Find Your Dream Machine Learning Job

About Netradyne

Founded in 2015, Netradyne is a technology company that leverages expertise in Artificial Intelligence, Deep Learning, and Edge Computing to bring transformational solutions to the transportation industry. Netradyne's technology is already deployed in thousands of vehicles; and our customers drive everything from passenger cars to semi-trailers on interstates, suburban roads, rural highways-even off-road.

Netradyne is looking for talented engineers to join our Analytics team comprised of graduates from IITs, IISC, Stanford, UIUC, UCSD etc. We build cutting edge AI solutions to enable drivers and fleets realize unsafe driving scenarios in real-time to prevent accidents from happening and reduce fatalities/injuries.

Role and Responsibilities

You will be embedded within a team of machine learning engineers and data scientists; responsible for building and productizing generative AI and deep learning solutions. You will:

• Design, develop, and evaluate generative AI models for vision and data science tasks.
• Collaborate with cross-functional teams to integrate AI-driven solutions into business operations.
• Build and enhance frameworks for automation, data processing, and model deployment.
• Develop and deploy AI agents, including Retrieval-Augmented Generation (RAG) systems.
• Utilize Gen-AI tools and workflows to improve the efficiency and effectiveness of AI solutions.
• Conduct research and stay updated with the latest advancements in generative AI and related technologies.

Requirements:

• B. Tech, M. Tech or PhD in computer science, electrical engineering, statistics or math.
• At least 8 years of working experience in data science, computer vision, or related domain.
• Proven experience with building and deploying generative AI solutions.
• Strong programming skills in Python and solid fundamentals in computer science, particularly in algorithms, data structures, and OOP.
• Experience with Gen-AI tools and workflows.
• Proficiency in both vision-related AI and data analysis using generative AI.
• Experience with cloud platforms and deploying models at scale.
• Experience with transformer architectures and large language models (LLMs).
• Familiarity with frameworks such as TensorFlow, PyTorch, and Hugging Face.
• Proven leadership and team management skills.

Desired Skills:

• Working experience with AWS is a plus.
• Knowledge of best practices in software development, including version control, testing, and continuous integration.
• Working knowledge of common industry frameworks and tools around building LLMs, such as OpenAI, GPT, BERT, etc.
• Experience with MLOps tools and practices for continuous deployment and monitoring of AI models.

Experience Level: 3-5 Years

Location: Bengaluru, India

About the Role:

We are looking for a driven and experienced Machine Learning Engineer to join our team and help push the boundaries of what's possible with Large Language Models (LLMs) and intelligent agents. This is a hands-on role for someone with a strong background in LLM tooling, evaluation, and data engineering, and a deep appreciation for building reusable, scalable, and open solutions.

You'll work across the stack-from agent and tool design, model evaluation, and dataset construction to serving infrastructure and fine-tuning pipelines. We're especially excited about candidates who have made meaningful contributions to open-source LLM/AI infrastructure and want to build foundational systems used by others across the ecosystem.

Key Responsibilities:

• Design, build, and iterate on LLM-powered agents and tools, from prototypes to production.
• Develop robust evaluation frameworks, benchmark suites, and tools to systematically test LLM behaviors.
• Construct custom evaluation datasets, both synthetic and real-world, to validate model outputs at scale.
• Build scalable, production-grade data pipelines using Apache Spark or similar frameworks.
• Work on fine-tuning and training workflows for open-source and proprietary LLMs.
• Integrate and optimize inference using platforms like vLLM, llama.cpp, and related systems.
• Contribute to the development of applications, emphasizing composability, traceability, and modularity.
• Actively participate in and contribute to open-source projects within the LLM/agent ecosystem.

Requirements:

Must-Have Skills:

• 3-5 years of experience in machine learning, with a strong focus on LLMs, agent design, or tool building.
• Demonstrable experience building LLM-based agents, including tool usage, planning, and memory systems.
• Proficiency in designing and implementing evaluation frameworks, metrics, and pipelines.
• Strong data engineering background, with hands-on experience in Apache Spark, Airflow, or similar tools.
• Familiarity with serving and inference systems like vLLM, llama.cpp, or TensorRT-LLM.
• Deep understanding of building componentized ML systems.

Open-Source Contributions:

• Proven track record of contributing to open-source repositories related to LLMs, agent frameworks, evaluation tools, or model training.
• Experience maintaining your own open-source libraries or tooling is a major plus.
• Strong Git/GitHub practices, code documentation, and collaborative PR workflows.
• You'll be expected to build tools, frameworks, or agents that may be released back to the community when possible.

Nice-to-Have:

• Familiarity with LLM orchestration frameworks like LangChain, CrewAI/AutoGen, Haystack, or DSPy.
• Experience training or fine-tuning models using LoRA, PEFT, or full-scale distributed training.
• Experience deploying LLM applications at scale in cloud or containerized environments (e.g., AWS, Kubernetes, Docker).

What We Offer:

• The opportunity to work on state-of-the-art LLM and agent technologies.
• Encouragement and support for open-source contributions as part of your day-to-day.
• A fast-paced, collaborative, and research-focused environment.
• Influence over architectural decisions in a rapidly evolving space.

To Apply:

Please submit your resume and links to your GitHub, open-source projects, or public technical writing (blog posts, talks, etc.) to

Job Title: AI/ML Intern

Location: Gurgaon, India

Employment Type: Internship (Paid)

Stipend: As per Industry Standards

About Aaizel Tech Labs

Aaizel Tech Labs is a pioneering tech startup at the intersection of cybersecurity, AI, geospatial solutions, and more. We are passionate about leveraging technology to develop high-performance products and cutting-edge solutions. As a growing startup, we seek dynamic individuals eager to work on transformative projects in AI and Machine Learning.

Role Overview

We are looking for a motivated AI/ML Intern to join our data science team. This internship offers hands-on experience with model development, data engineering, and deployment in real-world projects. You will collaborate with experienced professionals and contribute to initiatives spanning predictive analytics, computer vision, and more helping to shape the future of technology at Aaizel Tech Labs.

Key Responsibilities

1. Model Development & Optimization

• ML Model Implementation: Assist in designing, implementing, and deploying machine learning models for applications like predictive analytics and anomaly detection.

• Deep Learning Exposure: Gain experience with deep learning frameworks by working with CNNs, RNNs, and exploring generative models (GANs) on guided projects.

• Experimentation: Help run experiments and tune models using basic hyperparameter optimization techniques (Grid Search, etc.).

2. Data Engineering & Preprocessing

• Data Preparation: Support the collection, cleaning, and preprocessing of datasets using libraries like Pandas and NumPy.

• ETL Assistance: Assist in developing simple ETL pipelines to process data from diverse sources such as IoT sensors or satellite imagery.

• Integration: Learn to integrate data from APIs and databases to build comprehensive datasets for analysis.

3. Research & Algorithm Development

• Innovation Exposure: Research state-of-the-art machine learning techniques (e.g., Transfer Learning, Transformer models) and assist in applying these to ongoing projects.

• Algorithm Exploration: Participate in team discussions to brainstorm new approaches for solving real-world problems in cybersecurity, climate monitoring, or geospatial data analysis.

4. Deployment & MLOps

• Deployment Support: Gain hands-on experience deploying models using container technologies like Docker and basic CI/CD pipelines.

• Cloud Platforms: Assist in experiments with cloud platforms (AWS, Azure, or GCP) for scalable model serving solutions.

• Lifecycle Management: Learn best practices for model versioning, monitoring, and maintenance.

5. Performance Evaluation & Tuning

• Model Metrics: Help evaluate model performance using metrics such as F1 Score, AUCROC, and other domain-relevant measures.

• Tuning Assistance: Support the process of model tuning through guided experiments and parameter adjustments.

6. Collaboration & Code Quality

• Team Integration: Collaborate with data engineers, cybersecurity experts, and geospatial analysts to integrate AI solutions into end-to-end products.

• Coding Standards: Contribute to maintaining high-quality codebases by following best practices and using version control (Git).

• Documentation: Assist in documenting your work, including model specifications, experiments, and deployment processes.

7. Monitoring & Maintenance

• Dashboard Support: Participate in the creation of monitoring dashboards (using tools like Grafana or Prometheus) to track model performance.

• Feedback Loops: Help develop feedback mechanisms to retrain models based on real-time data and evolving application needs.

Skills & Qualifications

Required Qualifications:

• Currently pursuing or recently completed a Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field.

• Proficiency in Python and familiarity with libraries such as Pandas, NumPy, and scikit-learn. • Basic understanding of machine learning algorithms and experience (academic projects or internships) with model development.

• Exposure to one or more deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus.

• Ability to work collaboratively in a team-oriented environment.

• Strong analytical and problem-solving skills, with attention to detail.

• Good written and verbal communication skills.

Preferred Qualifications:

• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn) and basic dashboarding.

• Some experience with SQL and NoSQL databases.

• Interest in cloud platforms (AWS, Azure, or Google Cloud) and containerization (Docker).

• Knowledge of version control systems (Git) and basic CI/CD concepts.

• Prior internship or project experience in AI/ML is advantageous. Learning Opportunities

• Practical Projects: Work on real-world AI/ML projects that contribute directly to our product development.

• Mentorship: Benefit from one-on-one guidance from experienced data scientists and machine learning engineers.

• Skill Development: Gain exposure to industry-standard tools, frameworks, and best practices in AI and ML.

• Cross-Disciplinary Exposure: Collaborate with experts in cybersecurity, geospatial analysis, and data engineering.

• Career Growth: Develop your professional network and acquire skills that could lead to a full-time opportunity.

Application Process

Please submit your resume and a cover letter outlining your relevant experience and how you can contribute to Aaizel Tech Labs' success. Send your application to , or . Join Aaizel Tech Labs and be part of a team that's shaping the future of Big Data & AI-driven applications!

Designation: - ML / MLOPs Engineer

Location: - Noida (Sector- 132)

Key Responsibilities:

• Model Development & Algorithm Optimization: Design, implement, and optimize ML

models and algorithms using libraries and frameworks such as TensorFlow, PyTorch, and

scikit-learn to solve complex business problems.

• Training & Evaluation: Train and evaluate models using historical data, ensuring accuracy,

scalability, and efficiency while fine-tuning hyperparameters.

• Data Preprocessing & Cleaning: Clean, preprocess, and transform raw data into a suitable

format for model training and evaluation, applying industry best practices to ensure data

quality.

• Feature Engineering: Conduct feature engineering to extract meaningful features from data

that enhance model performance and improve predictive capabilities.

• Model Deployment & Pipelines: Build end-to-end pipelines and workflows for deploying

machine learning models into production environments, leveraging Azure Machine

Learning and containerization technologies like Docker and Kubernetes.

• Production Deployment: Develop and deploy machine learning models to production

environments, ensuring scalability and reliability using tools such as Azure Kubernetes

Service (AKS).

• End-to-End ML Lifecycle Automation: Automate the end-to-end machine learning

lifecycle, including data ingestion, model training, deployment, and monitoring, ensuring

seamless operations and faster model iteration.

• Performance Optimization: Monitor and improve inference speed and latency to meet real-

time processing requirements, ensuring efficient and scalable solutions.

• NLP, CV, GenAI Programming: Work on machine learning projects involving Natural

Language Processing (NLP), Computer Vision (CV), and Generative AI (GenAI),

applying state-of-the-art techniques and frameworks to improve model performance.

• Collaboration & CI/CD Integration: Collaborate with data scientists and engineers to

integrate ML models into production workflows, building and maintaining continuous

integration/continuous deployment (CI/CD) pipelines using tools like Azure DevOps, Git,

and Jenkins.

• Monitoring & Optimization: Continuously monitor the performance of deployed models,

adjusting parameters and optimizing algorithms to improve accuracy and efficiency.

• Security & Compliance: Ensure all machine learning models and processes adhere to

industry security standards and compliance protocols, such as GDPR and HIPAA.

• Documentation & Reporting: Document machine learning processes, models, and results to

ensure reproducibility and effective communication with stakeholders.Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related

field.

• 3+ years of experience in machine learning operations (MLOps), cloud engineering, or

similar roles.

• Proficiency in Python, with hands-on experience using libraries such as TensorFlow,

PyTorch, scikit-learn, Pandas, and NumPy.

• Strong experience with Azure Machine Learning services, including Azure ML Studio,

Azure Databricks, and Azure Kubernetes Service (AKS).

• Knowledge and experience in building end-to-end ML pipelines, deploying models, and

automating the machine learning lifecycle.

• Expertise in Docker, Kubernetes, and container orchestration for deploying machine

learning models at scale.

• Experience in data engineering practices and familiarity with cloud storage solutions like

Azure Blob Storage and Azure Data Lake.

• Strong understanding of NLP, CV, or GenAI programming, along with the ability to apply

these techniques to real-world business problems.

• Experience with Git, Azure DevOps, or similar tools to manage version control and CI/CD

pipelines.

• Solid experience in machine learning algorithms, model training, evaluation, and

hyperparameter tuning

About Mindtickle's AI/ML Engineering Team

Mindtickle is a revenue productivity solution that helps revenue teams enhance their performance by identifying areas for improvement for each team member, recommending appropriate remedial actions, and providing opportunities to implement those recommendations.

The charter of the CoE-ML team is to enhance Mindtickle's solution offerings-such as embedding artificial intelligence in the form of CoPilots, developing hyper-realistic AI-powered role plays, and enabling the automatic curation of collateral while also improving Mindtickle's internal operations. This includes optimizing workflows, accelerating business processes, and making information more easily discoverable. We work on cutting-edge technologies to drive innovation and deliver advanced AI solutions. We maintain high-quality evaluation standards and continuous improvement practices to ensure our AI features meet stringent performance and reliability criteria.

Role Overview

As an SDE-3 in AI/ML, you will:

• Translate business asks and requirements into technical requirements, solutions, architectures, and implementations.
• Define clear problem statements and technical requirements by aligning business goals with AI research objectives.
• Lead the end-to-end design, prototyping, and implementation of AI systems, ensuring they meet performance, scalability, and reliability targets.
• Architect solutions for GenAI and LLM integrations, including prompt engineering, context management, and agentic workflows.
• Develop and maintain production-grade code with high test coverage and robust CI/CD pipelines on AWS, Kubernetes, and cloud-native infrastructures.
• Establish and maintain post-deployment monitoring, performance testing, and alerting frameworks to ensure performance and quality SLAs are met.
• Conduct thorough design and code reviews, uphold best practices, and drive technical excellence across the team.
• Mentor and guide junior engineers and interns, fostering a culture of continuous learning and innovation.
• Collaborate closely with product management, QA, data engineering, DevOps, and customer facing teams to deliver cohesive AI-powered product features.

Key Responsibilities

Problem Definition & Requirements

• Translate business use cases into detailed AI/ML problem statements and success metrics.
• Gather and document functional and non-functional requirements, ensuring traceability throughout the development lifecycle.

Architecture & Prototyping

• Design end-to-end architectures for GenAI and LLM solutions, including context orchestration, memory modules, and tool integrations.
• Build rapid prototypes to validate feasibility, iterate on model choices, and benchmark different frameworks and vendors.

Development & Productionization

• Write clean, maintainable code in Python, Java, or Go, following software engineering best practices.
• Implement automated testing (unit, integration, and performance tests) and CI/CD pipelines for seamless deployments.
• Optimize model inference performance and scale services using containerization (Docker) and orchestration (Kubernetes).

Post-Deployment Monitoring

• Define and implement monitoring dashboards and alerting for model drift, latency, and throughput.
• Conduct regular performance tuning and cost analysis to maintain operational efficiency.

Mentorship & Collaboration

• Mentor SDE-1/SDE-2 engineers and interns, providing technical guidance and career development support.
• Lead design discussions, pair-programming sessions, and brown-bag talks on emerging AI/ML topics.
• Work cross-functionally with product, QA, data engineering, and DevOps to align on delivery timelines and quality goals.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of professional software development experience, with at least 3 years focused on AI/ML systems.
• Proven track record of architecting and deploying production AI applications at scale.
• Strong programming skills in Python and one or more of Java, Go, or C++.
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerized deployments.
• Deep understanding of machine learning algorithms, LLM architectures, and prompt engineering.
• Expertise in CI/CD, automated testing frameworks, and MLOps best practices.
• Excellent written and verbal communication skills, with the ability to distill complex AI concepts for diverse audiences.

Preferred Experience

• Prior experience building Agentic AI or multi-step workflow systems (using tools like Langgrah, CrewAI or similar).
• Familiarity with open-source LLMs (e.g., Hugging Face hosted) and custom fine-tuning.
• Familiarity with ASR (Speech to Text) and TTS (Text to Speech), and other multi-modal systems.
• Experience with monitoring and observability tools (e.g. Datadog, Prometheus, Grafana).
• Publications or patents in AI/ML or related conference presentations.
• Knowledge of GenAI evaluation frameworks (e.g., Weights & Biases, CometML).
• Proven experience designing, implementing, and rigorously testing AI-driven voice agents - integrating with platforms such as Google Dialogflow, Amazon Lex, and Twilio Autopilot - and ensuring high performance and reliability.

What We Offer

• Opportunity to work at the forefront of GenAI, LLMs, and Agentic AI in a fast-growing SaaS environment.
• Collaborative, inclusive culture focused on innovation, continuous learning, and professional growth.
• Competitive compensation, comprehensive benefits, and equity options.
• Flexible work arrangements and support for professional development.

Proficiency in ML frameworks (e.g., TensorFlow, PyTorch).

Experience with natural language processing (NLP) and large language models (LLMs).

Understanding of generative models and their applications.

Proficiency in programming languages such as Python, Go, or Java.

Experience in developing APIs and integrating AI models into existing systems.

Familiarity with containerization tools (e.g., Docker, Kubernetes).

Experience with (CI/CD) pipelines and databases or data lakes, and/or real-time data processing frameworks.

Job Responsibility:

GEN AI is must

Products.looking for a data scientist who will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver AI/ML based Enterprise Software Products.

• Develop solutions related to machine learning, natural language processing and deep learning & Generative AI to address business needs.

• Your primary focus will be in applying Language/Vision techniques, developing llm based applications and building high

quality prediction systems.

• Analyze Data: Collaborate with cross-functional teams to understand data requirements and identify relevant data sources.

Analyze and preprocess data to extract valuable insights and ensure

data quality.

• Evaluation and Optimization: Evaluate model performance using

appropriate metrics and iterate on solutions to enhance performance

and accuracy. Continuously optimize algorithms and models to

adapt to evolving business requirements.

• Documentation and Reporting: Document methodologies, findings, and outcomes in clear and concise reports. Communicate results effectively to technical and non-technical stakeholders.

Work experience background required:

• Experience building software from the ground up in a corporate or startup environment.

Essential skillsets required:

• 3-6 years experience in software development

• Educational Background: Strong computer science and

Math/Statistics

• Experience with Open Source LLM and Langchain Framework and

and designing efficient prompt for LLMs.

• Proven ability with NLP and text-based extraction techniques.

• Experience in Generative AI technologies, such as diffusion and/or

language models.

• Excellent understanding of machine learning techniques and

algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests,

etc.

• Familiarity with cloud computing platforms such as GCP or AWS.

Experience to deploy and monitor model in cloud environment.

• Experience with common data science toolkits, such as NumPy,

Pandas etc

• Proficiency in using query languages such as SQL

• Good applied statistics skills, such as distributions, statistical

testing, regression, etc.

• Experience working with large data sets along with data modeling,

language development, and database technologies

• Knowledge in Machine Learning and Deep Learning frameworks

(e.g., TensorFlow, Keras, Scikit-Learn, CNTK, or PyTorch), NLP,

Recommender systems, personalization, Segmentation,

microservices architecture and API development.

• Ability to adapt to a fast-paced, dynamic work environment and

learn new technologies quickly.

• Excellent verbal and written communication skills

Nielsen is seeking an organized, detail oriented, team player, to join the Engineering team in the role of Software ML Engineer. Nielsen's Audience Measurement Engineering platforms support the measurement of television viewing in more than 30 countries around the world. The Software Engineer will be responsible to define, develop, test, analyze, and deliver technology solutions within Nielsen's Collections platforms.

Required skills

• Bachelor's degree in Computer Science or equivalent degree
• 3+ years of software experience Experience with Machine learning frameworks and models
• Pytorch experience preferred Strong understanding of statistical analysis and mathematical data manipulation Work with web technology including Java, Python, JavaScript, React/Redux, Kotlin
• Follow best practices for software development and deployment.
• Understanding of relational database, big data, and experience in SQL.
• Proficient at using GIT, GitFlow, JIRA, Gitlab and Confluence. Strong analytical and problem solving skills
• Open-minded and passionate to learn and grow technology skills
• Strong sense of accountability Solution-focused and ability to drive change within the organization
• Experience in writing unit/integration tests including test automation
• Strong testing and debugging abilities, functional, analytical and technical abilities, ability to find bugs, attention to detail, troubleshooting

Additional Useful Skills

• A fundamental understanding of the AWS ecosystem (EC2, S3, EMR, Lambda, etc)
• Experienced in building RESTful APIs.
• Experience in writing unit/integration tests including test automation.

Location - Chennai / Mumbai / Pune / Hyderabad / Bangalore (Hybrid)

Notice Period - Immediate joiner to 30days

What You will do:

Play the role of Data Analyst / ML Engineer

Collection, cleanup, exploration and visualization of data

Perform statistical analysis on data and build ML models

Implement ML models using some of the popular ML algorithms

Use Excel to perform analytics on large amounts of data

Understand, model and build to bring actionable business intelligence out of data that is available in different formats

Work with data engineers to design, build, test and monitor data pipelines for ongoing business operations.

Basic Qualifications :

Experience: 4+ years.

Hands-on development experience playing the role of Data Analyst and/or ML Engineer.

Experience in working with excel for data analytics

Experience with statistical modelling of large data sets

Experience with ML models and ML algorithms

Coding experience in Python.

Nice to have Qualifications

Experience with wide variety of tools used in ML

Experience with Deep learning.

Benefits

Competitive salary.

Hybrid work model.

Learning and gaining experience rapidly.

Reimbursement for basic working set up at home.

Insurance (including a top up insurance for COVID).

About Alt Carbon: Alt Carbon is India's leading Carbon Removal (CDR) company. We blend science, technology & tradition to undertake climate action to turn the clock on historic emissions in the atmosphere. Our science and technology takes place in Bangalore; our operations are undertaken in Darjeeling's heritage tea estates.

Role Overview:

We are looking for a passionate Machine Learning Engineer to develop, deploy, and optimize ML models that enhance our carbon removal technologies. The ideal candidate will work cross-functionally with scientists, software engineers, and other experts to build AI-driven solutions that improve efficiency, accuracy, and scalability in carbon sequestration and monitoring.

What You'll Do:

• Machine Learning & AI Development
• Model Development: Train and optimize ML models for carbon sequestration monitoring, geospatial analytics, and predictive weathering rates.
• Deep Learning: Apply CNNs, transformers, and diffusion models for remote sensing and climate forecasting.
• Geospatial AI: Build ML-powered GIS tools, land-use change models, and soil mineralization estimations.
• Data Engineering & MLOps
• Scalable ML Pipelines: Develop large-scale data pipelines for climate, soil, and geospatial datasets using Airflow, Dask, or Spark.
• Cloud & Infrastructure: Deploy ML models on AWS, GCP, or Azure using Docker, Kubernetes, and CI/CD workflows.
• Big Data Processing: Work with satellite, drone, and sensor data for real-time carbon tracking.
• Geospatial & Climate Data Analysis
• Remote Sensing: Process data from Sentinel, Landsat, MODIS, LiDAR, integrating with Google Earth Engine (GEE) and QGIS.
• Geochemistry & Soil Science: Model mineral weathering, CO2 drawdown, and climate resilience impacts.
• Time-Series & Climate Data: Analyze NOAA, ERA5, CMIP6 datasets for climate pattern detection.

What We're Looking For:

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
• 3+ years of experience in machine learning, deep learning, or AI development.
• Python (NumPy, Pandas, PyTorch, TensorFlow, Scikit-learn)
• Cloud ML & MLOps (AWS, GCP, Azure, Kubernetes, Docker, CI/CD)
• Geospatial & Remote Sensing (GIS, Google Earth Engine, QGIS, Sentinel/Landsat)
• Big Data & Pipelines (Airflow, Dask, Spark, ETL, SQL, NoSQL)
• Deep Learning & Computer Vision (CNNs, Transformers, Self-Supervised Learning)
• Familiarity with geospatial data, climate modeling, or environmental science is a plus.
• Strong problem-solving skills and the ability to work in a collaborative team environment.

Preferred Qualifications:

• Experience in climate tech, sustainability, or carbon markets.
• Contributions to open-source ML or environmental science projects.
• Background in graph neural networks, diffusion models, or self-supervised learning.

Why Join Us?

There are innumerable JDs floated every day in Bangalore. How many of them will offer you an opportunity to work on something as challenging, meaningful, and important as Climate Change? And how many of them have operations in a place as beautiful, legendary, and special as Darjeeling?

We are looking for a highly skilled and results-driven Experienced Data Scientist to be at the forefront of developing and implementing Generative AI solutions that address critical business challenges and unlock new opportunities. This individual will leverage their deep expertise in data science, machine learning, and specifically Generative AI techniques to drive impactful projects from ideation to deployment. They will develop AI & ML solutions to tackle complex business challenges and facilitate data-driven decision-making through hands-on work with large datasets and strong collaboration with cross-functional teams to deliver significant results.

Responsibilities:

• Data Handling & Preparation: Work with diverse and large-scale datasets. Perform data cleaning, preprocessing, feature engineering, and create synthetic datasets as needed for training and evaluating Generative AI models. Ensure data quality and integrity throughout the model development lifecycle.
• Model Optimization & Deployment: Optimize Generative AI models for performance, scalability, efficiency, and responsible AI considerations (bias detection and mitigation, hallucination reduction). Collaborate with Machine Learning Engineers and DevOps teams to deploy models into production environments and establish monitoring frameworks.
• Prompt Engineering & Fine-tuning: Develop effective prompts and fine-tuning strategies for Large Language Models to achieve desired outputs and adapt models to specific domains and tasks.
• Generative AI Model Development & Implementation: Design, develop, train, fine-tune, and deploy various Generative AI models, including but not limited to Large Language Models (LLMs), diffusion models, Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs), for applications such as:
• Text generation (content creation, summarization, chatbots).
• Image and video synthesis.
• Code generation and assistance.
• Synthetic data generation and augmentation.
• Research & Innovation: Stay current with the latest research and advancements in the field of Generative AI, exploring new architectures, methodologies, and tools. Proactively identify and evaluate opportunities to apply cutting-edge Generative AI techniques to solve business problems.
• Experimentation & Evaluation: Design and execute rigorous experiments to evaluate the performance of Generative AI models using relevant metrics (e.g., BLEU, ROUGE, FID, perplexity). Analyze experimental results, identify areas for improvement, and iterate on model development based on findings.
• Collaboration & Communication: Work closely with product managers, software engineers, researchers, and business stakeholders to understand requirements, communicate technical findings, and translate complex AI concepts to non-technical audiences.
• Documentation & Knowledge Sharing: Maintain comprehensive documentation of all development processes, models, and experimental results. Share knowledge and best practices with the broader data science and engineering teams.
• Ethical AI Practices: Adhere to ethical AI principles and guidelines in the development and deployment of Generative AI models, with a focus on fairness, transparency, and accountability.

Machine Learning Lead - LLMs, GenAI & Conversational AI

Noida (Sector 63) - Hybrid (office-based role)

2+ years hands-on in LLM / Generative AI

5+ years overall in AI/ML or IT

Full-time

About the Role

Jupiter AI Labs is looking for a Machine Learning Lead to spearhead development and deployment of cutting-edge AI solutions across NLP, Vision, and Speech. You'll architect LLM & agentic-AI pipelines, build conversational agents, own CI/CD deployments, mentor junior engineers, and liaise directly with clients and stakeholders.

Key Responsibilities

End-to-end LLM Solutions : Lead design, fine-tuning & deployment of chatbots, multi-agent (A2A/MCP) workflows.

Open-Source Model Integration : Architect pipelines with Llama2, Mistral, Claude, GPT-series via Hugging Face, LangChain, etc.

AI Agent Orchestration : Build automations with N8N LangGraph.

Conversational AI : Develop assistants using Botpress, Rasa, Azure Bot Framework, AWS Lex.

Speech & Vision : Integrate ASR (Whisper, Coqui), TTS engines, and OCR models (Tesseract, PaddleOCR).

Full-Stack ML APIs : Develop FastAPI/Flask services, integrate into React/Node.js front ends.

Cloud CI/CD : Deploy scalable models on AWS/Azure/GCP, automate via Docker, Terraform, GitHub Actions.

Team Leadership : Mentor ML engineers, run daily standups, produce status reports.

Client Engagement : Represent Jupiter AI Labs in technical reviews, manage stakeholder expectations, deliver project documentation.

️ Required Skills & Experience

2+ years in LLM / Generative AI (prompt-engineering, fine-tuning, RAG).

Proficient with Hugging Face , LangChain, Transformers, vector databases.

Hands-on with agentic AI tools (LangGraph, CrewAI) and A2A/MCP pipelines.

Experience building conversational agents (Rasa, Botpress, Azure Bot, Lex).

Expertise in ASR and TTS integrations (Whisper, commercial APIs).

OCR modeling (Tesseract, PaddleOCR, Google Vision API).

Full-stack ML API development (FastAPI/Flask + React or Node).

Cloud deployment & CI/CD on AWS/Azure/GCP (Docker, Kubernetes, Terraform).

Workflow automation with N8N , or Zapier.

Computer Vision experience (YOLO, OpenCV, custom CNNs).

Strong understanding of MLOps practices, version control, and monitoring.

Proven track record running daily standups, reporting, and mentoring.

Soft Skills

Exceptional verbal & written English communication.

Collaborative leadership in cross-functional teams.

Highly organized, proactive, and deadline-driven.

Ability to train freshers and manage junior engineers.

Strong stakeholder management and client-facing presence.

Preferred Qualifications

B.Tech / M.Tech / Ph.D. in Computer Science, AI, or related field.

Open-source contributions (GitHub, Hugging Face Spaces).

Certifications in AI/ML (AWS, Google Cloud, etc.).

What We Offer

Exposure to breakthrough LLM, CV, ASR & GenAI projects.

Ownership of end-to-end architecture and experiments.

Fast-paced, learning-driven culture.

Competitive salary + performance bonuses.

Medical insurance, flexible work hours, and career growth path.

To apply, please share your resume, answers to the screening questions, and links to any relevant GitHub or project portfolios to ( ) . We look forward to building the future of AI together!

Job Title: Machine Learning Engineer Location: Gurgaon/NCR Job Type: Full-time Permanent Experience: 7-10 years

As a Machine Learning Engineer, you will be responsible for designing, implementing, and maintaining machine learning models and systems. This role involves collaborating with cross-functional teams to understand business needs and deliver data-driven solutions.

Required skills and qualifications:

• 8-10 years of experience in relevant fields.
• Strong programming skills in Python, R, or Java.
• Expertise in machine learning algorithms, techniques, and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (e.g., AWS, GCP) and distributed computing.

Responsibilities:

• Design, develop, and maintain machine learning models and pipelines.
• Collaborate with data scientists, engineers, and business stakeholders to identify needs and implement solutions.
• Translate business problems into data science and machine learning tasks.
• Ensure scalability and performance of ML solutions in production environments.
• Perform data preprocessing, feature selection, and model tuning.

Preferences:

• Experience with big data processing tools (e.g., Hadoop, Spark).
• Advanced degrees such as a master's or Ph.D. in Computer Science, Mathematics, Statistics, or related fields.

Don't miss the chance to work on cutting-edge ML projects with a top-tier team-apply now to be part of something impactful and fast-moving!

Job Title: Machine Learning Engineer

Reporting To: Technical Lead

Job Type: Full-time, Permanent

Location: Whitefield, Bangalore

ABOUT THE COMPANY

Formee Holdings is a multinational organization developing a portfolio of new and exciting brands in the tech and retail spaces. Formee Express, Formee, Tela Mela and Formee Jewlery are all brands under our umbrella; our fields of business are in e-commerce, EdTech and F&B industries.

We are currently headquartered in Melbourne, Australia, with offices also in India, Malaysia, Canada, China, Philippines, US, and UK. Needless to say, our teams are diverse and innovative!

At Formee Holdings, we value independence, flexibility, career and personal growth. We're a fast-growing Edu-tech company that embraces innovation and encourages our team members to push boundaries and reach new heights. With Formee Holdings, you will get an opportunity to work with a diverse team in different parts of the world. There is a huge potential for learning and growth.

JOB OVERVIEW

We are looking for a Machine Learning Engineer to design and build a conversational AI chatbot for public use. The chatbot will provide accurate, empathetic responses to a diverse audience, handling a wide range of queries while ensuring scalability, security, and accessibility. You'll collaborate with our technology and UX teams to create a tool that aligns with Formee's mission of community support.

The ideal candidate will have a strong background in building a conversational AI model and a passion for applying AI techniques to solve real-world problems.

KEY RESPONSIBILITIES

Model Development & Innovation:

• Design, prototype, and optimize scalable deep learning architectures focused on natural language understanding and generation.
• Leverage techniques such as reinforcement learning from human feedback (RLHF) and instruction tuning to enhance conversational performance.
• Experiment with prompt engineering and develop methodologies to improve model interpretability and alignment with user intent.

Research & Experimentation:

• Stay abreast of advances in NLP, deep learning, and generative AI by reviewing academic literature and industry trends.
• Lead proof-of-concept experiments and iterative development cycles to assess and validate novel approaches.

System Integration & Deployment:

• Collaborate with software and data engineers to integrate AI models into production pipelines using MLOps best practices.
• Monitor live systems for model drift and other performance issues; implement mechanisms for continuous improvement and retraining.

Cross-Functional Leadership:

• Work closely with product, design, and business teams to translate customer feedback and market trends into actionable technical requirements.
• Help set strategic roadmaps for AI research and guide development efforts in line with ethical AI principles and regulatory compliance.

SKILLS REQUIRED

Technical Expertise:

• Expertise in designing and training a deep learning model from scratch using frameworks such as Tensorflow or PyTorch.
• Hands-on experience in designing, training, and fine-tuning large-scale Neural Language Models.
• In-depth knowledge of deep learning architectures, particularly Transformer models, and familiarity with techniques like reinforcement learning from human feedback (RLHF) and instruction tuning.
• Proficiency in natural language processing (NLP) fundamentals, including attention mechanisms, context window management, and prompt engineering.
• Strong programming skills in Python and familiarity with modern data pipelines.

Experimental & Research Acumen:

• Demonstrable track record in conducting rigorous, iterative experiments-such as hyperparameter tuning, ablation studies, and performance benchmarking-to optimize model performance and alignment.
• A history of research contributions, which could include peer-reviewed publications, open-source contributions, or patents in areas related to AI, deep learning, or NLP.

Additional Skills and Traits:

• Strong mathematical foundation, especially in linear algebra, calculus, probability, and statistics, to support algorithm development and optimization.
• Ability to dive into complex, large codebases to debug, optimize, and iterate on models.

ABOUT YOU

• You're curious about new technologies and Artificial Intelligence and you are driven to find ways to implement them in your work.
• You have a big appetite to learn and improve your technical skills.
• You are analytical and you have a keen eye for detail.
• You have great problem-solving skills, and you work well in a team.
• You have knowledge of the entire web development process.
• Excited to use and explore new generative AI tools for software engineering tasks on a day-to-day basis.

AFour is part of ACL Digital, an ALTEN Group Company, which is a digital product innovation and engineering leader. We help our clients design and build innovative products (AI, Cloud, and Mobile ready), content and commerce-driven platforms, and connected, converged digital experiences for the modern world through a design-led Digital Transformation framework. By integrating our strategic design, engineering, and industry capabilities, we help our clients decode the digital world and accelerate their growth journey. Headquartered in Silicon Valley, ACL Digital is a leader in design-led digital experience, innovation, enterprise modernization, and product engineering services converging to Technology, Media & Telecom. We are a talented workforce and part of the 50,000+ employee ALTEN Group, spread across more than 30 countries, offering a multicultural workplace and a collaborative knowledge environment. In INDIA we have operations in Bangalore, Chennai, Pune, Panjim, Hyderabad, Noida and Ahmedabad. In the USA, we have offices in California, Atlanta, Philadelphia, and Washington states

Technical skills and competencies:

4-5 years of relevant experience

Training/Certification in Data Science/Machine Learning is preferred

Ability to effectively work with technical leads

Strong communication skills, ability to synthesize conclusions

Familiarity with Data Science concepts, Machine Learning algorithms & Libraries such as Scikit-learn, Numpy, Pandas, Stattools, Tensorflow, PyTorch, XGBoost

Worked in Machine Learning Training and Deployment pipelines

Worked in FastAPI/Falsk framework

Worked in Docker and Virtual Environment

Worked in Database Operations

Strong analytical and problem solving skills

Ability to thrive in a dynamic environment where there can be degrees of ambiguity

Candidate Profile and Competencies:

To be able to apply data mining, quantitative analysis, statistical techniques and conduct simultaneous experiments, to help us draw reliable insights from data.

To be able understand business use-cases and use various sources to collect and annotate datasets for the business problems.

To have a strong academic background with good analytical skill and exposure to machine learning and information retrieval domain and technologies

Strong programming skills, must be able to work in programming languages such as Python, C/C++, etc

Acquire data from primary or secondary data sources and perform data tagging

Filter and clean data as per the business requirement and maintain a well-defined, structured and clean database

Work on data labeling tool(s) and annotate data for machine learning models. Sift through structured and unstructured data; identify the right content and annotate with the right label

Interpret data, analyse results using statistical techniques and models and conduct exploratory analysis

Regards,

Komal Narole

Who are we?

Founded in 2014 by Khadim Batti and Vara Kumar, Whatfix is a leading global B2B SaaS provider and the largest pure-play enterprise digital adoption platform (DAP). Whatfix empowers companies to maximize the ROI of their digital investments across the application lifecycle, from ideation to training to the deployment of software. Driving user productivity, ensuring process compliance, and improving user experience of internal and customer-facing applications.

Spearheading the category with serial innovation and unmatched customer-centricity, Whatfix is the only DAP innovating beyond the category, positioning itself as a comprehensive suite for GenAI-powered digital adoption, analytics, and application simulation. Whatfix product suite consists of 3 products - Mirror, DAP and Analytics. This product suite helps businesses accelerate ROI on digital investments by streamlining application deployment across its lifecycle.

• Whatfix has seven offices across the US, India, UK, Germany, Singapore, and Australia and a presence across 40+ countries.
• Customers: 700+ enterprise customers, including over 85 Fortune 500 companies such as Shell, Microsoft, Schneider Electric, and UPS Supply Chain Solutions.
• Investors: Raised a total of $270 million. Most recently Series E round of $125 Million led by Warburg Pincus with participation from existing investor SoftBank Vision Fund 2
• Other investors include Cisco Investments, Eight Roads Ventures (A division of Fidelity Investments), Dragoneer Investments, Peak XV Partners, and Stellaris Venture Partners.

"Hustle Mode ON" is something we live by.

About the Role:

Whatfix is working on building an intelligent assistant that understands user actions and intent, acting as a helpful guide to enhance productivity. This assistant will anticipate user needs, provide actionable insights, and streamline task completion.

We are seeking a rockstar AI/ML Engineers who have experience in building world-class products. The ideal candidate will have a strong passion for leveraging AI and machine learning to create cutting-edge solutions that transform user experiences. If you thrive in solving complex problems, pushing the boundaries of AI/ML technology, and working collaboratively in a fast-paced environment, this role is for you!

Key Responsibilities:

• Develop advanced computer vision and state-of-the-art deep learning models to understand software applications and derive user intent.
• Research and implement ML and deep learning algorithms for production use.
• Build and maintain infrastructure for AI/ML systems, including model inference, automated (re-)training, monitoring, explainability, and more.
• Stay updated on cutting-edge AI research from leading labs by reading papers and experimenting with code.
• Assist AI product managers and business stakeholders in understanding the capabilities and limitations of AI for the products.
• Fine-tune, retrain, and scale existing model deployments.
• Conduct necessary ML tests and benchmarks for model validation.

Our Ideal candidate:

• Experience: 7+ years of expertise in machine learning.
• Deep Learning Expertise: Strong understanding of deep learning principles in both Computer Vision and Natural Language Processing (NLP).
• LLM Knowledge: Familiarity with LLM architectures like BERT and GPT, with hands-on experience fine-tuning these models for enhanced performance.
• Model Development: Proven experience in developing deep learning models, such as CNNs and Vision Transformers, for image-based tasks in production systems.
• Research and Application: Extensive experience in algorithms for image processing, content-based video/image analysis, object detection, segmentation, and tracking.
• Libraries: Proficiency in machine learning and deep learning libraries like PyTorch and Hugging Face.
• Technical Skills: Demonstrated ability to implement, improve, debug, and maintain machine learning models.

Nice to Have:

• Strong programming skills in Python.
• Expertise in optimization and debugging.
• Familiarity with version control systems such as Git.
• Self-motivated and responsible, with excellent written and verbal communication skills.
• Experience in handling and visualizing large datasets and creating performance reports.

Note:

• We strive to live and breathe our Cultural Principles and encourage employees to demonstrate some of these core values - Customer First; Empathy; Transparency; Fail Fast & Scale Fast; No Hierarchies for Communication; Deep Dive & Innovate; Trust, Do it as you own it;
• We are an equal opportunity employer and value diverse people because of and not in spite of the differences. We do not discriminate on the basis of race, religion, color, national origin, ethnicity, gender, sexual orientation, age, marital status, veteran status, or disability status

AI Ops Senior Architect - 12 - 17 Years

Pune/ Bengaluru/Hyderabad/Chennai/ Gurugram, India

Tredence is Data science, engineering, and analytics consulting company that partners with some of the leading global Retail, CPG, Industrial and Telecom companies. We deliver business impact by enabling last mile adoption of insights by uniting our strengths in business analytics, data science and data engineering.

Headquartered in the San Francisco Bay Area, we partner with clients in US, Canada, and Europe. Bangalore is our largest Centre of Excellence with skilled analytics and technology teams serving our growing base of Fortune 500 clients.

JOB DESCRIPTION

At Tredence, you will lead the evolution of "Industrializing AI" solutions for our clients by implementing ML/LLM/GenAI & Agent Ops best practices. You will lead the Architecture , Design & development of large scale ML/LLMOps platforms for our clients. You'll build and maintain tools for deployment, monitoring, and operations. You'll be a trusted advisor to our clients in ML/GenAI/Agent Ops space & coach to the ML engineering practitioners to build effective solutions to Industrialize AI solutions

THE IDEAL CANDIDATE WILL BE RESPONSIBLE FOR

AI Ops Strategy, Innovation, Research and Technical Standards

1. Conduct research and experiment with emerging AI Ops technologies and trends. Create POV's, POC's & present Proof of Technology to use latest tools, Technologies & services from Hyper scalers focussed on ML, GenAI & Agent Ops
2. Define and propose new technical standards and best practices for the organization's AI Ops environment.
3. Lead the evaluation and adoption of innovative MLOps solutions to address critical business challenges.
4. Conduct meet ups, attend & present in Industry events, conferences, etc
5. Ideate & develop accelerators to strengthen service offerings of AI Ops practice

Solution Design & Architectural Development

1. Lead Design & architecture of scalable model training & deployment pipelines for large-scale deployments
2. Architect & Design large scale ML & GenAI Ops platforms
3. Collaborate with Data science & GenAI practice to define and implement strategies of AI solutions for model explainability and interpretability
4. Mentor and guide senior architects in crafting cutting-edge AI Ops solutions
5. Lead architecture reviews and identify opportunities for significant optimizations and improvements.

Documentation and Best Practices

1. Develop and maintain comprehensive documentation of AIOps architectures designs and best practices.
2. Lead the development and delivery of training materials and workshops on AIOps tools and techniques.
3. Actively participate in sharing knowledge and expertise with the MLOps team through internal presentations and code reviews.

Qualifications and Skills:

1. Bachelor's or Master's degree in Computer Science, Data Science, or a related field with minimum 12 years of experience
2. Proven experience in architecting & developing AIOps solutions - to streamline Machine Learning & GenAI development lifecycle
3. Proven experience as an AI Ops Architect - ML & GenAI in architecting & design of ML & GenAI platforms
4. Hands on experience in Model deployment strategies, Designing ML & GenAI model pipelines to scale in production, Model Observability techniques used to monitor performance of ML & LLM's
5. Strong coding skills with experience in implementing best coding practices

Technical Skills & Expertise

• Python, PySpark, PyTorch ,Java, Micro Services, API's
• LLMOps - Vector DB, RAG, LLM Orchestration tools, LLM Observability, LLM Guardrails, Responsible AI
• MLOps - MLFlow, ML/DL libraries, Model & Data Drift Detection libraries & techniques
• Real Time & Batch Streaming
• Container Orchestration Platforms
• Cloud platforms - Azure/ AWS/ GCP, Data Platforms - Databricks/ Snowflake

Nice to Have:

• Understanding of Agent Ops
• Exposure to Databricks platform

You can expect to -

• Work with world's biggest Retailers, CPG's, HealthCare, Banking & Manufacturing customers and help them solve some of their most critical problems
• Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
• Work in a diverse environment that keeps evolving
• Hone your entrepreneurial skills as you contribute to growth of the organization

We are hiring a, high-agency ML/AI Engineer to architect and deliver cutting-edge AI solutions for our enterprise clients. This isn't just another ML engineering role - you'll be the technical owner driving complex AI projects end-to-end, from ideation through production deployment and ongoing monitoring and improvement.

You'll spend your time:

• 50% building robust, scalable AI systems that solve real business problems
• 25% researching and prototyping innovative solutions using the latest AI advances
• 25% collaborating with clients and stakeholders to translate business needs into technical solutions

About thinkbridge

thinkbridge is how growth-stage companies can finally turn into tech disruptors. They get a new way there - with world-class technology strategy, development, maintenance, and data science all in one place. But solving technology problems like these involves a lot more than code. That's why we encourage think'ers to spend 80% of their time thinking through solutions and 20% coding them. With an average client tenure of 4+ years, you won't be hopping from project to project here - unless you want to. So, you really can get to know your clients and understand their challenges on a deeper level. At thinkbridge, you can expand your knowledge during work hours specifically reserved for learning. Or even transition to a completely different role in the organization. It's all about challenging yourself while you challenge small thinking.

thinkbridge is a place where you can:

1. Think bigger - because you have the time, opportunity, and support it takes to dig deeper and tackle larger issues.
2. Move faster - because you'll be working with experienced, helpful teams who can guide you through challenges, quickly resolve issues, and show you new ways to get things done.
3. Go further - because you have the opportunity to grow professionally, add new skills, and take on new responsibilities in an organization that takes a long-term view of every relationship.

thinkbridge there's a new way there.

Why This Role Is Different

• True Ownership: You'll be the technical architect making critical design decisions, not just implementing someone else's vision
• Production Focus: We need someone who's deployed models/systems AND kept them running - monitoring drift, handling failures, improving performance
• Diverse Projects: From GenAI applications (65%) to classical ML solutions (35%), across Retail, HRTech, Fintech, and Healthcare domains
• Technical Architecture: Design systems and guide implementation decisions without the overhead of formal people management

What is expected of you?

As part of the job, you will be required to

• Architect end-to-end ML/AI solutions that actually work in production
• Build and maintain production-grade systems with proper monitoring, alerting, and continuous improvement
• Make strategic technical decisions on approach, tools, and implementation
• Translate complex AI concepts into business value for clients
• Set technical direction for project teams through architecture and best practices
• Stay current with AI research and identify practical applications for client problems

If your beliefs resonate with these, you are looking at the right place!

• Accountability -Finish what you started
• Communication-Context aware, pro-active, and clean communication
• Outcome -High throughput
• Quality -High-Quality work and consistency
• Ownership -Go Beyond

Requirements

Must have technical skills

• Strong Python proficiency with production ML experience
• Hands-on experience deploying AND maintaining ML systems in production
• Experience with both GenAI (LLMs, RAG systems) and classical ML techniques
• Understanding of ML monitoring, drift detection, and model lifecycle management
• Cloud deployment experience (Azure knowledge helpful; AWS experience highly valued)
• Containerization and basic MLOps practices

Good to have technical skills

• Experience fine-tuning open-source models to match/beat proprietary models
• Advanced MLOps (CI/CD for ML, A/B testing, feature stores)
• Published work (papers, blogs, open-source contributions)
• Experience with streaming/real-time ML systems

What We're Really Looking for

Beyond technical skills, we need someone who:

• Takes initiative and drives projects without waiting for instructions
• Has actually felt the pain of their own technical decisions in production
• Can explain "why this approach" to both engineers and business stakeholders
• Thinks critically about when to use (and when NOT to use) GenAI
• Has opinions about ML best practices based on real experience

Our Flagship Policies and Benefits:

• Work from anywhere!
• Flexible work hours
• All leaves taken are paid leaves
• Family Insurance
• Quarterly Collaboration Week

Machine Learning Engineer - Infrastructure

Job Description:

As a Machine Learning Engineer specializing in infrastructure at Restored Cloud, you will design and build the tools, frameworks, and systems that enable efficient training, deployment, and scaling of machine learning models. You will work on cutting-edge challenges in model optimization, infrastructure automation, and distributed computing to support high-performance AI/ML workflows. Your work will directly impact how engineers train and deploy large-scale models seamlessly and reliably.

Responsibilities:

• Develop and maintain ML infrastructure for distributed model training and inference.
• Implement tools for model versioning, experiment tracking, and automated deployments.
• Optimize ML pipelines to improve training and inference efficiency at scale.
• Collaborate with data scientists and engineers to integrate ML workflows with existing systems.
• Monitor and ensure the reliability, security, and performance of the ML infrastructure.
• Ability to adapt to new technologies and take on new responsibilities and roles in a fast-paced growing company.

Qualifications:

• Experience with ML frameworks like TensorFlow, PyTorch, or JAX.
• Knowledge of MLOps tools such as MLflow, Kubeflow, or Airflow.
• Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes).
• Strong programming skills in Python and familiarity with CI/CD pipelines.
• Understanding of distributed training methods and hardware acceleration (e.g., GPUs, TPUs).
• Worked with LLMs and models over 10B parameters.
• 5+ years of experience in Machine Learning, Systems Engineering, or a related field.

About VOIS:

VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value and enhancing quality and efficiency across 28 countries, and operating from 7 locations: Albania, Egypt, Hungary, India, Romania, Spain and the UK.

Over 29,000 highly skilled individuals are dedicated to being Vodafone Group's partner of choice for talent, technology, and transformation. We deliver the best services across IT, Business Intelligence Services, Customer Operations, Business Operations, HR, Finance, Supply Chain, HR Operations, and many more.

Established in 2006, VOIS has evolved into a global, multi-functional organisation, a Centre of Excellence for Intelligent Solutions focused on adding value and delivering business outcomes for Vodafone.

About VOIS India:

In 2009, VOIS started operating in India and now has established global delivery centres in Pune, Bangalore and Ahmedabad. With more than 14,500 employees, VOIS India supports global markets and group functions of Vodafone, and delivers best-in-class customer experience through multi-functional services in the areas of Information Technology, Networks, Business Intelligence and Analytics, Digital Business Solutions (Robotics & AI), Commercial Operations (Consumer & Business), Intelligent Operations, Finance Operations, Supply Chain Operations and HR Operations and more

Role: ML/GenAI Engineer

Experience: 7-10 Years

Job Location: Pune, EON IT Park (Hybrid)

Must have skills: ML/AI/GenAI, Python, GCP, Github, LLM

Job Summary:

We are seeking a highly skilled and motivated Machine Learning Engineer / GenAI Engineer to join our AI/ML team. The ideal candidate will have hands-on experience in building, deploying, and maintaining machine learning models and GenAI solutions using modern cloud platforms and MLOps practices. You will work closely with cross-functional teams to design scalable AI pipelines and integrate LLM-based solutions into production environments.

Key Responsibilities:

• Design, develop, and deploy ML and GenAI solutions using Python and LLM frameworks.
• Build and manage ML pipelines using Vertex AI Pipelines and CI/CD tools like Cloud Build and GitHub Actions.
• Containerize applications using Docker and manage deployments on Google Cloud Platform (GCP) and Azure.
• Collaborate with data engineers and DevOps teams to ensure seamless integration and deployment.
• Write and maintain infrastructure as code using YAML.
• Implement and manage CI/CD pipelines for ML workflows.
• Work with GitHub for version control and collaboration.
• Ensure model governance and compliance using protocols like Model Context Protocol and A2A Protocol.
• Participate in code reviews, design discussions, and team planning sessions.

Mandatory Skills:

• Strong hands-on experience with Python.
• Proficiency in Google Cloud Platform (GCP) and Azure Cloud.
• Experience with Vertex AI Pipelines.
• Expertise in CI/CD setup, Cloud Build, and GitHub Actions.
• Proficient in Docker and container orchestration.
• Experience with YAML for configuration and infrastructure.
• Familiarity with LLM models and GenAI tools.
• Strong team collaboration and version control using GitHub.

Good-to-Have Skills:

• GCP Certifications (e.g., Professional ML Engineer, Cloud Architect).
• Strong communication skills for cross-functional collaboration.
• Experience with Azure Data Factory.
• Knowledge of Model Context Protocol and A2A Protocol.
• Familiarity with Google ADK (AI Development Kit).
• Exposure to React for building front-end interfaces.

VOIS Equal Opportunity Employer Commitment

India:

VOIS is proud to be an Equal Employment Opportunity Employer. We celebrate differences and we welcome and value diverse people and insights. We believe that being authentically human and inclusive powers our employees' growth and enables them to create a positive impact on themselves and society. We do not discriminate based on age, colour, gender (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, race, religion, sexual orientation, status as an individual with a disability, or other applicable legally protected characteristics.

As a result of living and breathing our commitment, our employees have helped us get certified as a Great Place to Work in India for four years running. We have been also highlighted among the Top 5 Best Workplaces for Diversity, Equity, and Inclusion, Top 10 Best Workplaces for Women, Top 25 Best Workplaces in IT & IT-BPM and 14th Overall Best Workplaces in India by the Great Place to Work Institute in 2023. These achievements position us among a select group of trustworthy and high-performing companies which put their employees at the heart of everything they do.

By joining us, you are part of our commitment. We look forward to welcoming you into our family which represents a variety of cultures, backgrounds, perspectives, and skills!

Apply now, and we'll be in touch!

TE-9 Years and above

Location-Bangalore

NP-Immediate-15 days

• Lead the design, development, and deployment of AI-based automation tools for data artifact migration.
• Develop machine learning models to intelligently map, transform, and validate data across different big data platforms.
• Build robust data pipelines to handle high-volume, high-velocity data migration.
• Collaborate with data engineers and architects to integrate AI-driven solutions into existing data workflows.
• Implement NLP and pattern recognition algorithms to automate schema conversion and data validation.
• Design custom algorithms for automated data quality checks and anomaly detection.
• Mentor junior engineers and contribute to technical leadership within the AI engineering team.
• Stay updated with the latest advancements in AI, big data technologies, and automation frameworks.
• Create comprehensive technical documentation and best practice guidelines for AI-based data migration.

Details on tech stack

• Splunk
• ClickHouse
• Grafana
• Data Migration Automation

About Us:

Grid Dynamics (Nasdaq:GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, India, Central and Eastern Europe.

To learn more about Grid Dynamics, please visit . Follow us on Facebook , Twitter , and LinkedIn .

We at STGYA are seeking a highly motivated and skilled AI/ML Engineer with a strong focus on training and fine-tuning Large Language Models (LLMs), Vision Language Models (VLMs), and Small Language Models (SLMs).

The ideal candidate will possess a deep understanding of deep learning principles, experience with state-of-the-art model architectures, and a proven track record of developing and deploying high-performance AI models. You will play a crucial role in advancing our AI capabilities and contributing to the development of innovative AI-powered products and services.

Responsibilities:

Model Training and Fine-tuning: Design, implement, and optimize training pipelines for LLMs, VLMs, and SLMs using large-scale datasets.

• Experiment with various training techniques, including transfer learning, reinforcement learning, and parameter-efficient fine-tuning (PEFT).
• Evaluate and improve model performance using relevant metrics and benchmarks.
• Address model biases and ensure fairness and robustness.

Model Architecture and Development: Research and implement cutting-edge model architectures and techniques for LLMs, VLMs, and SLMs.

• Adapt and customize existing models to meet specific application requirements.
• Develop and maintain efficient code for model training and inference.

Data Management and Processing: Work with large-scale datasets, including text, images, and multimodal data.

• Develop data preprocessing and augmentation pipelines to improve model performance.
• Collaborate with data engineers to ensure data quality and availability.

Infrastructure and Deployment: Optimize model training and inference for performance and scalability.

• Deploy trained models to production environments.
• Monitor and maintain deployed models.
• Work with cloud based infrastructure such as AWS, GCP, or Azure.

Research and Development: Stay up-to-date with the latest advancements in AI/ML, particularly in LLMs, VLMs, and SLMs.

• Contribute to research projects and publications.
• Collaborate with other researchers and engineers to develop innovative AI solutions.

Collaboration and Communication: Work closely with cross-functional teams, including product managers, data scientists, and software engineers.

• Communicate technical concepts and findings effectively to both technical and non-technical audiences.
• Document all work clearly and effectively.

Qualifications:

• Technical Skills: Strong understanding of deep learning principles and techniques.
• Extensive experience with training and fine-tuning LLMs, VLMs, and SLMs.
• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Experience with transformer-based architectures (e.g., BERT, GPT, T5, ViT).
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure).
• Proficiency in Python and other relevant programming languages.
• Experience with version control systems (e.g., Git).

Preferred Skills: Experience with distributed training and large-scale model deployment.

• Knowledge of natural language processing (NLP), computer vision, and multimodal learning.
• Experience with reinforcement learning.
• Experience with prompt engineering.
• Experience with model quantization and pruning.

Soft Skills:

• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a team.
• Strong passion for AI and machine learning.
• Ability to adapt to fast changing technologies.

Branch Overview

Branch delivers world-class financial services to the mobile generation. With offices in the United States, Nigeria, Kenya, and India, Branch is a for-profit socially conscious company that uses the power of data science to reduce the cost of delivering financial services in emerging markets. We believe that everyone everywhere deserves fair financial access. The rapid spread of smartphones presents an opportunity for the world's emerging middle class to access banking options and achieve financial flexibility.

Branch's mission-driven team is led by the founder and former CEO of Kiva.org. The company presents a rich opportunity for our team members to drive meaningful growth in rapidly evolving and changing markets. In 2019, Branch announced our Series C and garnered more than $100M in funding with investments from leading Silicon Valley firms, including Andreessen Horowitz, Trinity Capital, Foundation Capital, Visa, and the International Finance Corporation (IFC).

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As a product-driven org, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we create an environment where everyone feels empowered to propose solutions to the challenges we face.

We value diversity and are committed to providing an inclusive working environment where human beings of all backgrounds can thrive.

Job Overview

Branch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.

Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.

Responsibilities

• Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.
• Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.
• Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.
• Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.

Qualifications

• 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.
• Excellent software engineering and programming skills, especially Python and SQL.
• A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.
• A deep understanding of using cloud computing infrastructure and data pipelines in production.
• Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.
• Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.
• The drive to make a positive impact on customers' lives.

Benefits of Joining

• Mission-driven, fast-paced, and entrepreneurial environment
• Competitive salary and equity package
• A collaborative and flat company culture
• Fully-paid Group Medical Insurance and Personal Accidental Insurance
• Unlimited paid time off, including personal leave, bereavement leave, and sick leave
• Fully paid parental leave - 6 months maternity leave and 3 months paternity leave
• Monthly WFH stipend alongside a one-time home office set-up budget
• $500 Annual professional development budget
• Team meals and social events - Virtual and In-person

We're looking for more than just qualifications if you're unsure that you meet the criteria but identify with our vision of providing equal opportunity to everyone to access financial services, please do not hesitate to apply!

Branch International is an Equal Opportunity Employer. The company does not and will not discriminate in employment on any basis prohibited by applicable law.

Job Title: GenAI / ML Engineer

Function: Research & Development

Location: Delhi/Bangalore (3 days in office)

About the Company:

Elucidata is a TechBio Company headquartered in San Francisco. Our mission is to make life sciences data AI-ready. Elucidata's Elucidata's LLM-powered platform Polly, helps research teams wrangle, store, manage and analyze large volumes of biomedical data. We are at the forefront of driving GenAI in life sciences R&D across leading BioPharma companies like Pfizer, Janssen, NextGen Jane and many more. We were recognised as the 'Most Innovative Biotech Company, 2024', by Fast Company. We are a 120+ multi-disciplinary team of experts based across the US and India. In September 2022, we raised $16 million in our Series A round led by Eight Roads, F-Prime, and our existing investors Hyperplane and IvyCap.

About the Role:

We are looking for a GenAI / ML Engineer to join our R&D team and work on cutting-edge applications of LLMs in biomedical data processing. In this role, you'll help build and scale intelligent systems that can extract, summarize, and reason over biomedical knowledge from large bodies of unstructured text, including scientific publications, EHR/EMR reports, and more.

You'll work closely with data scientists, biomedical domain experts, and product managers to design and implement reliable GenAI-powered workflows - from rapid prototypes to production-ready solutions. This is a highly strategic role as we continue to invest in agentic AI systems and LLM-native infrastructure to power the next generation of biomedical applications.

Key Responsibilities:

• Build and maintain LLM-powered pipelines for entity extraction, ontology normalization, Q&A, and knowledge graph creation using tools like LangChain, LangGraph, and CrewAI.
• Fine-tune and deploy open-source LLMs (e.g., LLaMA, Gemma, DeepSeek, Mistral) for biomedical applications.
• Define evaluation frameworks to assess accuracy, efficiency, hallucinations, and long-term performance; integrate human-in-the-loop feedback.
• Collaborate cross-functionally with data scientists, bioinformaticians, product teams, and curators to build impactful AI solutions.
• Stay current with the LLM ecosystem and drive adoption of cutting-edge tools, models, and methods.

Qualifications:

• 2-3 years of experience as an ML engineer, data scientist, or data engineer working on NLP or information extraction.
• Strong Python programming skills and experience building production-ready codebases.
• Hands-on experience with LLM frameworks and tooling (e.g., LangChain, HuggingFace, OpenAI APIs, Transformers).
• Familiarity with one or more LLM families (e.g., LLaMA, Mistral, DeepSeek, Gemma) and prompt engineering best practices.
• Strong grasp of ML/DL fundamentals and experience with tools like PyTorch, or TensorFlow.
• Ability to communicate ideas clearly, iterate quickly, and thrive in a fast-paced, product-driven environment.

Good to Have (Preferred but Not Mandatory)

• Experience working with biomedical or clinical text (e.g., PubMed, EHRs, trial data).
• Exposure to building autonomous agents using CrewAI or LangGraph.
• Understanding of knowledge graph construction and integration with LLMs.
• Experience with evaluation challenges unique to GenAI workflows (e.g., hallucination detection, grounding, traceability).
• Experience with fine-tuning, LoRA, PEFT, or using embeddings and vector stores for retrieval.
• Working knowledge of cloud platforms (AWS/GCP) and MLOps tools (MLflow, Airflow etc.).
• Contributions to open-source LLM or NLP tooling

We are proud to be an equal-opportunity workplace and are an affirmative action employer. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.

Job Summary: We are seeking a talented and motivated Machine Learning Engineer to join our team. The ideal candidate will have a strong background in machine learning algorithms, data analysis, and software development. You will be responsible for designing, developing, and deploying machine learning models and systems that drive our products and services.

Key Responsibilities:

• Develop and implement machine learning algorithms and models.
• Design and conduct experiments to evaluate the performance of machine learning models.
• Collaborate with cross-functional teams to integrate machine learning solutions into products.
• Analyze large datasets to extract meaningful insights and patterns.
• Optimize and tune machine learning models for performance and scalability.
• Monitor and maintain deployed models, ensuring their performance in a production environment.
• Stay up-to-date with the latest trends and advancements in machine learning and artificial intelligence.
• Write clean, maintainable, and efficient code.
• Document processes, experiments, and results comprehensively.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• Proven experience as a Machine Learning Engineer or similar role.
• Strong understanding of machine learning algorithms and techniques (e.g., supervised and unsupervised learning, reinforcement learning, deep learning).
• Proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with data preprocessing and feature engineering techniques.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) is a plus.
• Strong problem-solving skills and the ability to work independently and as part of a team.
• Excellent communication and collaboration skills.

Preferred Qualifications:

• Experience with natural language processing (NLP) and computer vision.
• Knowledge of big data technologies (e.g., Hadoop, Spark).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience with version control systems (e.g., Git).
• Understanding of DevOps practices and CI/CD pipelines.

Sprinklr is the unified platform for all customer-facing functions. We call it unified customer experience management (Unified-CXM). We help companies deliver human experiences to every customer, every time, across any modern channel, at a once impossible scale. Headquartered in New York City with over 2,400 employees globally, Sprinklr works with more than 1,000 of the world's most valuable enterprises- global brands like Microsoft, P&G, Samsung, and more than 50% of the Fortune 100.

Role: In your role as a Lead / Senior Lead Product Engineer(Machine Learning) with us, you will be tasked with creating and delivering novel Machine Learning solutions for next generation of digital customer experience applications.

What will you do:

• Work in a collaboration of machine learning engineers and data scientists.
• Work on various disciplines of machine learning including but not limited to variety of disciplines including deep learning, reinforcement learning, computer vision, language, speech processing etc.
• Work closely with product management and design to define project scope, priorities and timelines.
• Work closely with machine learning leadership team to define and implement the technology and architectural strategy.
• Take partial ownership of project technical roadmap, which includes deciding, planning, publishing schedules, milestones, technical solution engineering, risks/mitigations, course corrections, trade-outs delivery.
• Deliver and maintain high-quality scalable systems in a timely and cost-effective manner.
• Recognising potential use-cases of cutting edge research in Sprinklr products and implementing your own solutions for the same.
• Stay updated on industry trends, emerging technologies, and advancements in data science, incorporating relevant innovations into the team's workflow.

What makes you qualified:

• Degree in Computer Science or related quantitative field of relevant experience from Tier 1 colleges.
• At least 5 years of Deep Learning Experience with a distinguished track record on technically fast paced projects.
• Familiarity with cloud deployment technologies, such as Kubernetes or Docker containers.
• Experience with large language models (GPT-4, Pathways, Google Bert, Transformer) and deep learning tools (TensorFlow, Torch).
• Working experience of software engineering best practices including coding standards, code reviews, SCM, CI, build processes, testing, and operations.
• Experience in communicating with users, other technical teams, and product management to understand requirements, describe software product features, and technical designs.

Nice to have:

• Experience in directly managing a team of high calibre machine learning engineers and data scientists.
• Experience with Multi-Modal ML including Generative AI.
• Interested in and thoughtful about the impacts of AI technology.
• A real passion for AI!

Job Summary:

We are looking for highly motivated and analytical Machine Learning Engineers with 1-3 years of experience in building scalable, production-ready AI/ML models. This role involves working on complex business problems using advanced ML/DL techniques across domains such as Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Generative AI.

You will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, DevOps, and product.

Location: Noida / Gurugram / Indore / Bengaluru / Pune / Hyderabad

Experience: 1-3 Years

Education: BE / B.Tech / M.Tech / MCA /

Key Responsibilities:

Model Development & Experimentation

• Design and build machine learning models for NLP, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques.
• Conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection.
• Apply statistical analysis to validate and interpret model results.
• Evaluate models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, AUC-ROC).

Data Handling & Feature Engineering

• Process large structured and unstructured datasets using Python, Pandas, and DataFrame APIs.
• Perform feature extraction, transformation, and selection tailored to specific ML problems.
• Implement data augmentation and enrichment techniques to enhance training quality.

Model Deployment & Productionization

• Deploy trained models to production environments using cloud platforms such as AWS (especially SageMaker).
• Containerize models using Docker and orchestrate deployments with Kubernetes.
• Implement monitoring, logging, and automated retraining pipelines for model health tracking.

Collaboration & Innovation

• Collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment.
• Explore and adopt cutting-edge AI/ML methodologies and GenAI frameworks (e.g., LangChain, GPT-3).
• Contribute to documentation, versioning, and knowledge-sharing across teams.
• Drive innovation and continuous improvement in AI/ML delivery and engineering practices.

Mandatory Technical Skills:

• Languages & Tools: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch)
• Model Development: Deep Learning, NLP, Time Series, Computer Vision
• Cloud Platforms: AWS (especially SageMaker)
• Model Deployment: Docker, Kubernetes, REST APIs
• ML Ops: Model monitoring, performance logging, CI/CD
• Frameworks: LangChain (for GenAI), Transformers, Hugging Face

Preferred / Good to Have:

• Experience with Foundation Model tuning and prompt engineering
• Hands-on with Generative AI (GPT-3/4, OpenAI APIs, LangChain integrations)
• Certifications: AWS Certified Machine Learning - Specialty
• Experience with version control (Git), and experiment tracking tools (MLflow, Weights & Biases)

Soft Skills:

• Excellent communication and presentation abilities
• Strong analytical and problem-solving mindset
• Ability to work in collaborative, fast-paced environments
• Curiosity to learn emerging technologies and apply them to real-world problems

Verint is a leader in CX automation. The world's most iconic brands rely on our open platform and team of AI-powered bots to create tangible AI business outcomes, now.

Today's organizations face skyrocketing expectations for delivering better customer experiences (CX) across every channel. But hiring more workers and increasing workforce expenses isn't a sustainable option.

AI offers a solution - and that's where Verint comes in. We empower brands with groundbreaking AI via our next-gen open platform. The first of its kind, Verint Open Platform helps organizations increase CX automation to achieve their strategic objectives and realize significant ROI.

The Verint Open Platform provides a team of AI-powered bots to augment human staff across the enterprise, including contact centers, web/mobile channels, branches, back offices, CX offices, and more. The result? Organizations can create capacity, lower costs, and continually improve CX.

It's all possible with CX automation.

Center of Excellence in Financial Analytics and Innovation

Team Description: The Center of Excellence in Financial Analytics comprises a dynamic and diverse team of professionals with expertise in finance, computer science, data analytics, data engineering, machine learning & AI, and FP&A. Our team is dedicated to driving innovation, leveraging analytics techniques, and utilizing financial insights to optimize decision-making within the organization. Collaborative and driven, our team members work closely together to deliver high-quality business insights and contribute to the success of the CFO Organization.

Location: Bangalore India

Job Title: Specialist - Machine Learning and AI

Job Summary:

We are seeking a highly skilled and motivated Specialist - Machine Learning and AI to join our Financial Analytics Center of Excellence in Bangalore. This role will support cross-functional business teams-including CFO, CTO/Product Analytics, Investor Relations, Corporate FP&A, Customer Success, Sales Operations, Reporting & Consolidation, and Partner Alliances-by designing and deploying advanced AI/ML solutions to solve complex business challenges.

The ideal candidate will bring 5-10 years of hands-on experience in applying machine learning and artificial intelligence in financial analytics, product usage analysis, and general business operations in a B2B software/SaaS environment.

Job Description:

• Collaborate with finance, product, and operations stakeholders to understand business questions and deliver ML/AI-driven solutions that improve forecasting, anomaly detection, and process automation.
• Lead the design and deployment of machine learning models including supervised, unsupervised, and reinforcement learning approaches to solve use cases in revenue forecasting, GL mapping, customer expansion recommendations, customer retention, churn and product analytics.
• Own the end-to-end ML pipeline: data preparation, feature engineering, model selection, training, validation, and deployment.
• Design and implement MLOps and automation pipelines to streamline the deployment and monitoring of ML models.
• Enhance and maintain existing models for intelligent classification to support business growth.
• Partner with data engineers and analysts to ensure data quality, scalable architecture, and secure model integration with business applications and dashboards.
• Provide thought leadership in identifying emerging AI/ML trends and proactively propose innovative use cases to improve business outcomes.
• Generate explainable, transparent outputs that can be translated into business actions and executive-level insights.

Required Qualifications:

• Bachelor's or master's degree in computer science, Data Science, Applied Mathematics, Statistics, or a related field.
• 5-10 years of hands-on experience applying machine learning and AI in a business context, preferably in the software/SaaS industry.
• Strong programming skills in Python and libraries like scikit-learn, XGBoost, TensorFlow, PyTorch, etc.
• Demonstrated success with ML use cases such as: GL classification, predictive modeling for financial KPIs, customer behavior prediction, or recommendation systems.
• Experience working in cross-functional teams with finance, sales, customer success, and product functions.
• Proficiency in SQL and working with structured/unstructured datasets.
• Ability to communicate complex technical solutions clearly to non-technical stakeholders and executive audiences.

Preferred Qualifications:

• Prior experience supporting FP&A, Product Analytics, or GTM Strategy functions.
• Exposure to cloud-based ML deployment (Azure, AWS, or GCP).
• Basic knowledge of Large Language Models (LLMs) and Generative AI tools.
• Familiarity with BI tools such as Power BI or Tableau for integrating ML output into business reporting.

Why Join Us?

• Be part of a growing, high-impact Financial Analytics Center of Excellence.
• Work on meaningful business challenges using cutting-edge AI/ML approaches.
• Collaborate with senior business leaders across Business Finance, Product, and Customer organizations.
• Drive innovation and help shape the next phase of our AI/ML capability in a dynamic business team in global software company.

Company Description:

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose - to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description:

The Staff ML Scientist will work with a team to conduct world-class Applied AI research on data analytics and contribute to the long-term research agenda in large-scale data analytics and machine learning, as well as deliver innovative technologies and insights to Visa's strategic products and business. This role represents an exciting opportunity to make key contributions to Visa's strategic vision as a world-leading data-driven company. The successful candidate must have strong academic track record and demonstrate excellent software engineering skills. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.

Essential Functions:

• Formulate business problems as technical data problems while ensuring key business drivers are collected in collaboration product stakeholders.
• Work with product engineering to ensure implement-ability of solutions. Deliver prototypes and production code based on need.
• Experiment with in-house and third-party data sets to test hypotheses on relevance and value of data to business problems.
• Build needed data transformations on structured and un-structured data.
• Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, analytics, and statistical techniques.
• Devise and implement methods for adaptive learning with controls on efficiency, methods for explaining model decisions where vital, model validation, A/B testing of models.
• Devise and implement methods for efficiently monitoring model efficiency and performance in production.
• Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.
• Contribute to development and adoption of shared predictive analytics infrastructure.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Basic Qualifications:

• 7+ years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

Preferred Qualifications:

• 7 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD

• Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks.

• Ability to program in one or more scripting languages such as Perl or Python and one or more programming languages such as Java, C++, or C#.

• Experience with one or more common statistical tools such SAS, R, KNIME, MATLAB.

• Deep learning experience with TensorFlow is a plus.

• Experience with Natural Language Processing is a plus.

• Experience working with large datasets using tools like Hadoop, MapReduce, Pig, or Hive is a must.

• Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.

Job Title: Senior Data Scientist (Remote - India) - Predictive Modeling & Machine Learning

Location: Remote (India)

Job Type: Full-time

Experience: 5+ YearsJob Summary:

We are looking for a highly skilled Senior Data Scientist to join our India-based team in a remote capacity. This role focuses on building and deploying advanced predictive models to influence key business decisions. The ideal candidate should have strong experience in machine learning, data engineering, and working in cloud environments, particularly with AWS.

You'll be collaborating closely with cross-functional teams to design, develop, and deploy cutting-edge ML models using tools like SageMaker, Bedrock, PyTorch, TensorFlow, Jupyter Notebooks, and AWS Glue. This is a fantastic opportunity to work on impactful AI/ML solutions within a dynamic and innovative team.Key Responsibilities:

Predictive Modeling & Machine Learning

• Develop and deploy machine learning models for forecasting, optimization, and predictive analytics.
• Use tools such as AWS SageMaker, Bedrock, LLMs, TensorFlow, and PyTorch for model training and deployment.
• Perform model validation, tuning, and performance monitoring.
• Deliver actionable insights from complex datasets to support strategic decision-making.

Data Engineering & Cloud Computing

• Design scalable and secure ETL pipelines using AWS Glue.
• Manage and optimize data infrastructure in the AWS environment.
• Ensure high data integrity and availability across the pipeline.
• Integrate AWS services to support the end-to-end machine learning lifecycle.

Python Programming

• Write efficient, reusable Python code for data processing and model development.
• Work with libraries like pandas, scikit-learn, TensorFlow, and PyTorch.
• Maintain documentation and ensure best coding practices.

Collaboration & Communication

• Work with engineering, analytics, and business teams to understand and solve business challenges.
• Present complex models and insights to both technical and non-technical stakeholders.
• Participate in sprint planning, stand-ups, and reviews in an Agile setup.

Preferred Experience (Nice to Have):

• Experience with applications in the utility industry (e.g., demand forecasting, asset optimization).
• Exposure to Generative AI technologies.
• Familiarity with geospatial data and GIS tools for predictive analytics.

Qualifications:

• Master's in Computer Science, Statistics, Mathematics, or a related field.
• 5+ years of relevant experience in data science, predictive modeling, and machine learning.
• Experience working in cloud-based data science environments (AWS preferred).

Job Description:

We are seeking an experienced Data Scientist with expertise in advanced machine learning techniques to join our dynamic team. The ideal candidate will have hands-on experience developing and deploying models using ensemble methods and other cutting-edge ML algorithms, mostly in the US banking domain.

Key Responsibilities:

• Develop and help deploy advanced machine learning models, including ensemble techniques, for customer lifecycle use cases (e.g., prescreen, acquisition, account management, collections, and fraud).
• Collaborate with cross-functional teams to define, develop, and improve predictive models that drive business decisions.
• Work with large datasets, utilizing tools like Python and SQL, to extract, clean, and transform data for modeling purposes.
• Ensure model robustness, interpretability, and scalability within banking environments.
• Strong problem-solving skills with the ability to handle complex datasets and turn them into actionable insights.

Key terms: artificial intelligence, research and engineering, large-language-models, speech-to-text, healthcare, startup, electronic health records.

About Mercurie

Simpler and smarter healthcare for everyone.

At Mercurie, we are fundamentally redesigning the digital health infrastructure, leveraging the recent breakthroughs in AI. Our health assistants will provide a one-stop interface to converse about patient health. We aim to create better connections between doctors and patients, leading to healthier, happier outcomes.

In the first stage of our product, we are helping doctors spend less time on typing and more time with patients by turning conversations into crystal-clear, comprehensive, and detailed medical notes that aid in:

• reduced follow-up queries and potential misunderstandings.
• faster claims processing.
• more inclusive care.
• education and research.

In the next stage, we plan to build a sophisticated medical record query engine.

Job Description

We are looking for a Senior/Staff AI Engineer to join our early-stage team. In this role, you would be in charge of developing, evaluating, and tuning AI services such as speech-to-text, document summarization, graph query engine, and agentic tooling. As an early member, you would have a large influence on the development of our product and the core technology of our platform, and a significant say in the direction our firm takes.

Qualifications

• This role would require owning a significant part of our product. Therefore, experience building and leading enterprise AI projects is essential. 5-10 years of experience would be preferred.
• Strong academic record (9+ on scale of 10) in a technical field such as Computer Science, Maths, Physics, or Electrical Engineering from a top-tier institute, such as the IITs.

Technical skills

• Experience with training and inference engines for large language, speech-to-text, and text-to-speech models. Examples include HuggingFace Transformers, ONNX, GGML and CTranslate2.
• Experience with Retrieval-Augmented Generation, Agentic AI, or the Model Context Protocol.
• The ability to build a functional AI (micro-)service from an idea is essential.
• Experience with GPU programming.
• Experience with graph databases.
• (Bonus) Experience working with health records and familiarity with modern AI algorithms on health records.

As an early-stage startup, we will pay attention to

• Communication and soft skills: we will work as a close-knit team with professionals from varied backgrounds, and being able to explain your domain knowledge effectively is essential.
• Ambition and creative thinking: maintaining rapid growth would require passion towards the product we are building, and contributing to ideas that would keep us at the top of the game.
• Flexibility and adaptability: at times, we may have to deviate from our original product plans as we explore product-market-fit further.
• Leadership skills: as the venture grows, you may soon start leading a team of engineers.

Compensation

• 25L in cash + 25L in equity (at seed valuation) per year (may vary based on experience and skills).
• On joining, four years of equity will be allocated and paid with a four-year vesting schedule.

Application Process

• Please write an application email to with the subject 'Job Application for Senior Machine Learning Engineer'.
• Please attach your CV and write a short 2-paragraph cover letter in the application email describing your interest in this role, and how your experience and skills are a good fit.
• If you have any open-source software contributions, please share the links in your application.
• We will try to get back to you within 2 weeks if you are shortlisted.
• If we receive more applications than we can handle, we may not be able to respond to you if you are not shortlisted. We apologise in advance for this.
• On getting shortlisted, expect an introductory call/meeting followed by 3-4 technical rounds.

To check more job openings, please visit

We are seeking a highly motivated and experienced ML Engineer/Data Scientist to join our growing ML/GenAI team.

You will play a key role in designing, developing and productionalizing ML applications by evaluating models, training and/or fine tuning them. You will play a crucial role in developing Gen AI based solutions for our customers. As a senior member of the team, you will take ownership of projects, collaborating with engineers and stakeholders to ensure successful project delivery.

What we're looking for:

• At least 3 years of experience in designing & building AI applications for customer and deploying them into production
• At least 5 years of Software engineering experience in building Secure, scalable and performant applications for customers.
• Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI.
• Design, develop, and operationalize existing ML models by fine tuning, personalizing it.
• Evaluate machine learning models and perform necessary tuning.
• Develop prompts that instruct LLM to generate relevant and accurate responses.
• Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.
• Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.
• Hands on customer experience with RAG solution or fine tuning of LLM model.
• Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.
• Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment.
• Proven experience building and deploying machine learning models in production environments for real life applications
• Good understanding of natural language processing, computer vision or other deep learning techniques.
• Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).
• Familiarity with Google Cloud or any other Cloud Platform and its machine learning services.
• Excellent communication, collaboration, and problem-solving skills.

Good to Have

• Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.
• Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure.
• Experience with Amazon Lex or Google DialogFlow CX or Microsoft Copilot studio for CCAI Agent workflows
• Experience with AutoML and vision techniques.
• Master's degree in statistics, machine learning or related fields.

Position: Machine Learning Engineer - Graph AI/Neo4j

Location: Hyderabad, India - Hybrid Remote (3 days in office, 2 days remote)

Experience: 2+ years

Employment Type: Full-time

Position Overview:

We are seeking a talented and experienced Machine Learning Engineer with a strong background in graph databases, particularly Neo4j, to join our dynamic team. The ideal candidate will be instrumental in developing and enhancing our knowledge bases and Retrieval-Augmented Generation (RAG) models, driving the accuracy and efficiency of our AI-powered solutions. You will play a key role in deploying cutting-edge models that enhance the AI features of our end-user applications, ensuring they meet the evolving needs of our customers.

Key Responsibilities

• Develop and support machine learning models with a focus on graph-based data and Neo4j.
• Build and maintain Python scripts and data pipelines for processing and analyzing graph data.
• Work with Large Language Models (LLMs) and retrieval-augmented generation (RAG) techniques as part of the ML workflow.
• Collaborate with backend and data teams to integrate graph AI solutions into applications.
• Write clean, reusable code and participate in code reviews.
• Support deployment and basic monitoring of ML models in production.
• Document workflows and solutions for team knowledge sharing.

Must-Have Qualifications

• 2+ years of experience in Machine Learning or Data Science using Python.
• Experience working with at least one graph database (preferably Neo4j) for data modeling and basic queries.
• Good understanding of machine learning fundamentals (regression, classification, basic model evaluation).
• Exposure to using or integrating LLMs (OpenAI, HuggingFace, or similar) with data workflows.
• Basic knowledge of retrieval-augmented generation (RAG) concepts.
• Familiarity with Python data libraries (pandas, scikit-learn, etc.).
• Ability to work with RESTful APIs.
• Familiarity with version control (Git) and writing simple unit tests.

Nice to Have

• Hands-on experience building or optimizing graph ML models (e.g., node classification, link prediction).
• Exposure to vector search or hybrid search techniques.
• Experience deploying Python code or ML models using Docker or basic cloud services (AWS, GCP, Azure).
• Experience working in a SaaS or multi-tenant application environment.

Key Skills

Python, Machine Learning, Graph Databases (Neo4j), LLM, RAG, Data Pipelines, Git, REST API

About Clear Demand: Clear Demand is the leader in AI-driven price and promotion optimization for retailers. Our platform transforms pricing from a challenge to a competitive advantage, helping retailers make smarter, data-backed decisions across the entire pricing lifecycle. By integrating competitive intelligence, pricing rules, and demand modelling, we enable retailers to maximize profit, drive growth, and enhance customer loyalty - all while maintaining pricing compliance and brand integrity. With Clear Demand, retailers stay ahead of the market, automate complex pricing decisions, and unlock new opportunities for growth.

Key Responsibilities:

• People management - Lead a team of software engineers, DS, DE, MLE, in the design, development, and delivery of software solutions.
• Program management - Strong program leader that has run program management functions to efficiently deliver ML projects to production and manage its operations.
• Work with Business stakeholders & customers in the Retail Business domain to execute the product vision using the power of AI/ML.
• Scope out the business requirements by performing necessary data-driven statistical analysis.
• Set goals and, objectives using proper business metrics and constraints.
• Conduct exploratory analysis on large volumes of data, understand the statistical shape, and use the right visuals to drive & present the analysis.
• Analyse and extract relevant information from large amounts of data and derive useful insights on a big-data scale.
• Create labelling manuals and work with labellers to manage ground truth data and perform feature engineering as needed.
• Work with software engineering teams, data engineers and ML operations team (Data Labellers, Auditors) to deliver production systems with your deep learning models.
• Select the right model, train, validate, test, optimise neural net models and keep improving our image and text processing models.
• Architecturally optimize the deep learning models for efficient inference, reduce latency, improve throughput, reduce memory footprint without sacrificing model accuracy.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
• Create and enhance model monitoring system that could measure data distribution shifts, alert when model performance degrades in production.
• Streamline ML operations by envisioning human in the loop kind of workflows, collect necessary labels/audit information from these workflows/processes, that can feed into improved training and algorithm development process.
• Maintain multiple versions of the model and ensure the controlled release of models.
• Manage and mentor junior data scientists, providing guidance on best practices in data science methodologies and project execution.
• Lead cross-functional teams in the delivery of data-driven projects, ensuring alignment with business goals and timelines.
• Collaborate with stakeholders to define project objectives, deliverables, and timelines.

Qualifications & Experience:

• MS/PhD from reputed institution with a delivery focus.
• 5+ years of experience in data science, with a proven track record of delivering impactful data-driven solutions.
• Delivered AI/ML products/features to production.
• Seen the complete cycle from Scoping & analysis, Data Ops, Modelling, MLOps, Post deployment analysis.
• Experts in Supervised and Semi-Supervised learning techniques. Hands-on in ML Frameworks - Pytorch or TensorFlow.
• Hands-on in Deep learning models. Developed and fine-tuned Transformer based models. (Input output metric, Sampling technique)
• Deep understanding of Transformers, GNN models and its related math & internals.
• Exhibit high coding standards and create production quality code with maximum efficiency.
• Hands-on in Data analysis & Data engineering skills involving Sqls, PySpark etc.
• Exposure to ML & Data services on the cloud - AWS, Azure, GCP Understanding internals of computer hardware - CPU, GPU, TPU is a plus.
• Can leverage the power of hardware accel to optimize the model execution -PyTorch Glow, cuDNN, is a plus

Vivaran Creations is a leading startup incubator founded with a mission to empower entrepreneurs and businesses. Led by CEO Damodari Balaji, Vivaran Creations specializes in providing technical assistance, executive management support, and strategic guidance to transform ideas into successful ventures. We're a young and passionate team focused on transforming ideas into scalable digital products.

Role Overview:

We are offering a hybrid, monthly paid internship for enthusiastic and skilled individuals passionate about artificial intelligence and machine learning. You'll work on real-time projects involving data, AI models, and smart applications, contributing to practical innovations for business clients.

Key Responsibilities:

• Assist in the development and deployment of AI/ML models.
• Collect, clean, and process datasets for analysis.
• Apply statistical methods and ML algorithms to solve business problems.
• Participate in model evaluation, fine-tuning, and performance optimization.
• Stay updated with current research and trends in AI/ML.
• Collaborate in hybrid mode: remote development and on-site team reviews/sync-ups.

Requirements:

• Pursuing/completed degree in Computer Science, AI, Data Science, or related fields.
• Solid foundation in Python and libraries such as Pandas, NumPy, scikit-learn.
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Strong analytical and problem-solving skills.
• Good communication skills and ability to work in a hybrid team environment.

What You'll Get:

• Monthly stipend.
• Real-world AI/ML project exposure.
• Mentorship from experienced professionals.
• Certificate and letter of recommendation.

Role Description: Principal Machine Learning Scientist(IC) - AdTech

About the Team:

Nykaa's AdTech Data Science team is at the forefront of building intelligent, ML-powered advertising products including Sponsored Products, Display Ads, and Creative Personalization. We aim to serve highly relevant, personalized ads to millions of users while maximizing advertiser success through scalable, automated systems. In this Principal IC role, you will be a hands-on technical leader-driving the development of foundational ML models and systems that fuel our ad platform. You'll work closely with product, engineering, and business teams to define and solve high-impact problems in advertising science.

What Are We Looking For?

Education:

• Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, Statistics, or a related technical field from a reputable institution.

Experience:

• 10+ years of experience building production-grade ML systems, with 5+ years specifically in AdTech, performance marketing, or large-scale recommender systems.
• Proven track record of delivering impactful ML innovations as a senior individual contributor, from ideation to deployment.
• Deep expertise in one or more of the following domains:
• CTR/CVR prediction, bidding dynamics, bid/budget optimization
• Multi-objective learning, campaign automation, target ROAS modeling
• Generative AI for creative optimization, personalization, or agentic workflows

Technical Skills:

• Advanced understanding of ML algorithms, reinforcement learning, Bayesian optimization, multi-armed bandits, and game theory as applied to digital advertising.
• Fluency in Python and ML frameworks like PyTorch, TensorFlow, XGBoost, and libraries like LightGBM, Scikit-learn.
• Expertise in large-scale data processing with PySpark, SQL etc...
• Experience with real-time inference, latency-sensitive model serving, and model monitoring in production environments.
• Strong command of A/B testing design, incrementality measurement, and online experimentation in AdTech systems.

Soft Skills:

• Passion for solving ambiguous, complex problems with scientific rigor and business impact.
• Deep ownership mentality and the ability to independently scope and drive projects end-to-end.
• Clear, concise communication of complex technical concepts to cross-functional stakeholders.
• Collaborative mindset with a track record of influencing product direction through technical thought leadership.

Responsibilities:

ML Development & Deployment:

• Design and develop cutting-edge models for predicting ad outcomes, bidding decisions, budget pacing, and SKU/ad selection.
• Build intelligent automation systems for campaign management that adapt in real-time to advertiser and platform feedback.
• Develop generative models to optimize ad creatives and improve user engagement across formats.

System Architecture & Optimization:

• Own the architecture of core components like model pipelines, simulation frameworks, and personalization layers within the ad platform.
• Drive research into long-term value modeling, multi-touch attribution, and campaign lifecycle optimization.

Cross-Functional Impact:

• Collaborate with Product and Engineering to design features that are ML-first and measurable.
• Act as the primary technical stakeholder for experimentation, metrics design, and long-term roadmap planning.

Thought Leadership & Innovation:

• Explore and prototype novel approaches using Reinforcement Learning, RLHF, contrastive learning, or LLMs for advertiser assistance or campaign agents.
• Publish internal whitepapers or contribute to external publications and IP generation when applicable.

Why Join Nykaa AdTech?

• Be a key technical architect behind Nykaa's growing AdTech ecosystem.
• Work on cutting-edge problems that intersect ML, economics, personalization, and creative optimization.
• Shape the future of advertising in India's leading beauty and lifestyle platform-with a strong focus on user delight and advertiser success.

Position- Senior Machine Learning Engineer

Experience - 6 to 9 years

Job Location - Pune / Remote

Immediate Joiner Only

Role Overview

• Strong experience in Computer Vision, NLP, Generative AI demonstrated through relevant projects or research.
• Proficiency in programming languages such as Python and libraries/frameworks like TensorFlow, PyTorch, OpenCV, spaCy, etc. and cloud AI services Aws/Azure/GCP
• Proven ability to bridge the gap between technical concepts and business impact, with a clear understanding of how data science aligns with business goals.
• Excellent communication skills to effectively convey complex technical concepts to both technical and non-technical stakeholders.

Nice to have:

• GCP Professional Machine Learning Engineer certification (not older than a year)
• Experience with work in iGaming industry

Responsibilities:

• Drive/Participate the ideation, development, and execution of POCs and AI related project
• Develop and implement machine learning models, algorithms, and data-driven solutions to address complex business problems
• Collaborate cross-functionally with engineering, product management, and other relevant teams to integrate data-driven functionalities into our products.

Job Title: Machine Learning Engineer

Location: Bengaluru (Hybrid)

Experience: 4-8 years

About Wissen Infotech

Wissen Infotech has been a trusted leader in the IT Services industry for over 25 years, delivering high-quality solutions to a global clientele. Within Wissen, the AI Center of Excellence (AI-CoE) was conceptualized to drive cutting-edge research and innovation, enabling us to build our own products and intellectual property. This team focuses on solving complex business challenges using AI while setting new benchmarks for reliable and scalable AI solutions.

Position Overview

We are seeking a passionate Machine Learning Engineer to join our AI-CoE team. This is a unique opportunity for individuals who are software engineers at heart and are driven to design, develop, and deploy robust AI systems. You will work on innovative projects, including building agentic systems, leveraging state-of-the-art technologies to create scalable and reliable distributed systems.

Key Responsibilities

• Design and develop scalable machine learning models and deploy them in production environments.

• Build and implement agentic systems that can autonomously analyze tasks, process large volumes of unstructured data, and provide actionable insights.

• Collaborate with data scientists, software engineers, and domain experts to integrate AI capabilities into cutting-edge products and solutions.

• Develop deterministic and reliable AI systems to address real-world challenges.

• Create and optimize scalable, distributed ML pipelines.

• Perform data preprocessing, feature engineering, and model evaluation to ensure high performance and reliability.

• Stay abreast of advancements in AI technologies and incorporate them into business solutions.

• Participate in code reviews, contribute to system architecture discussions, and continuously enhance project workflows.

Required Skills and Qualifications

• Software Engineering Fundamentals: Strong foundation in algorithms, data structures, and scalable system design.

• Education: Bachelor's or Master's degree in Computer Science, Engineering, or related fields with a solid academic track record.

• Experience: 4-8 years of hands-on experience in building AI systems or machine learning applications.

• Agentic Systems: Proven experience in developing systems that utilize AI agents for automating complex workflows, analyzing unstructured data, and generating actionable outcomes.

• Programming: Proficiency in programming languages such as Python, Java, or Scala.

• AI Expertise: Experience with machine learning frameworks like TensorFlow, PyTorch, or Hugging Face libraries (e.g., for working with transformer-based models and LLMs).

• MLOps Knowledge (preferred): Familiarity with tools like MLflow, Kubeflow, Airflow, Docker, or Kubernetes.

• Cloud Platforms: Hands-on experience with AWS, Azure, or Google Cloud for deploying machine learning models.

• Big Data: Experience with data processing tools and platforms such as Apache Spark or Hadoop.

• Problem-Solving: Strong analytical and problem-solving skills, with the ability to create robust solutions for complex challenges.

• Collaboration and Communication: Excellent communication skills to articulate technical ideas effectively to both technical and non-technical stakeholders.

What We Offer

• An opportunity to work with cutting-edge AI technologies and solve challenging business problems.

• A collaborative, innovative, and inclusive work culture.

• Continuous learning opportunities and access to advanced research.

• Competitive salary and comprehensive benefits

Responsive is looking for an ML Engineer with a strong background in Python, NLP, structured and unstructured data, and basic understanding of ML and DL algorithms/frameworks. The ideal candidate will have a Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics. The ML Engineer should be familiar with Linux and Git and have strong problem-solving and analytical skills. Additionally, the candidate should have a good understanding of mathematics.

Essential Responsibilities

• To develop and implement ML models and algorithms that improve the company's products and services.
• To Work with large datasets to analyze, model, and interpret data.
• To create and optimize NLP models to extract meaningful insights from unstructured text data.
• To collaborate with cross-functional teams to identify and solve complex business problems.
• To continuously monitor and improve the performance of ML models.
• To develop and maintain ML codebase, including version control using Git.

Education

Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics.

Experience

• 4-6 years of experience in Machine Learning
• Proficiency in Python is a must

Knowledge, Ability & Skills

• Comfortable with NLP techniques.
• Basic understanding of ML and DL algorithms/frameworks.
• Familiarity with Linux and Git.
• Good problem-solving and analytical skills.
• Good understanding of mathematics.

About RISA

Cancer patients don't just fight the disease - they fight the system. Today, life-saving treatments are routinely delayed by days or even weeks due to manual, error-prone workflows. At RISA Labs, we're here to fix that.

RISA's platform - Business Operating System as a Service (BOSS) - is not another automation bot or AI assistant. It's a full-stack orchestration engine built for the vertical complexity of healthcare. Instead of relying on humans to push paperwork or brittle bots that break when systems change, BOSS decomposes complex workflows into micro-tasks, then delegates them to a network of intelligent agents: LLMs, digital twins, and reinforcement learners, extending across an institution's entire software stack. This allows BOSS to create a parallel digital workforce, operating on behalf of teams and alongside them. A 1,000-person institution can function like a 2,000-person one overnight, with digital agents making up half the workforce.

Role Overview

We are seeking a talented Machine Learning Engineer who will work closely with data scientists, product managers, and engineers to implement machine learning solutions that solve real-world problems in industries like healthcare. You will focus on designing and building scalable, efficient machine learning systems, improving model performance, and driving innovation within RISA Labs' AI-driven platform.

This is an exciting opportunity to apply your skills in a high-impact, mission-driven environment and help shape the future of AI-powered infrastructure.

Responsibilities

• Model Development: Design, implement, and optimize machine learning models, including supervised/unsupervised learning, deep learning, and reinforcement learning
• Model Deployment: Work on the end-to-end lifecycle of machine learning models - from training and validation to deployment, monitoring, and continuous improvement in production environments
• Data Analysis & Feature Engineering: Analyze large datasets, clean and preprocess data, and identify key features to improve model accuracy and performance
• Performance Optimization: Continuously improve and optimize machine learning models for speed, scalability, and accuracy, focusing on real-time applications in high-volume environments
• Collaboration: Collaborate with cross-functional teams to integrate machine learning models into RISA's platform, ensuring that they meet business needs and user requirements
• Research & Innovation: Stay up-to-date with the latest research and industry trends in machine learning and AI, bringing new ideas and techniques to improve our systems
• Infrastructure Development: Work on building scalable infrastructure for machine learning workflows, including data pipelines, model management, and performance tracking
• AI Ethics & Compliance: Ensure that machine learning models are ethically sound and comply with industry regulations, such as HIPAA, when applied to sensitive data in regulated industries

Qualifications

• 3+ years of experience in machine learning engineering, data science, or related fields
• Proficiency in Python and machine learning frameworks like TensorFlow, PyTorch, or scikit-learn
• Solid experience with machine learning algorithms, model optimization, and deep learning techniques
• Experience with cloud platforms (AWS, GCP, or Azure) and deploying machine learning models in production
• Strong understanding of data structures, algorithms, and computational complexity
• Familiarity with distributed computing tools (e.g., Spark, Hadoop) and data pipelines
• Experience with model versioning, experiment tracking, and building machine learning workflows (e.g., MLflow, Kubeflow)
• Familiarity with data privacy and security standards (e.g., HIPAA) when working with sensitive data
• Excellent communication skills and the ability to work collaboratively in a cross-functional team
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field, or equivalent experience
• Bonus: Experience working in healthcare, life sciences, or other regulated industries

EGNYTE YOUR CAREER. SPARK YOUR PASSION.

"Please refrain from applying to this position if you don't meet the qualifications, such as being newly graduated/interns or having limited experience"

Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 17,000 customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you're not just landing a new career, you become part of a team of Egnyters who doers, thinkers, and collaborators are who embrace and live by our values:

Invested Relationships

Fiscal Prudence

Candid Conversations

ABOUT EGNYTE

Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 22,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere. For more information, visit .

ABOUT THE ROLE

Egnyte is seeking a Principal Machine Learning Engineer to drive innovation and leadership across machine learning initiatives, with a special emphasis on NLP solutions. As a Principal Engineer, you will play a pivotal role in shaping the future of AI/ML at Egnyte by defining technical strategy, overseeing complex machine learning architectures, and ensuring seamless integration of ML solutions into our platform at scale. You will mentor and guide engineering teams while providing expertise in state-of-the-art ML practices, ensuring a robust production pipeline and the professional management of ML models.

WHAT YOU'LL DO:

• Leading the technical strategy and execution for machine learning projects across the organization.
• Driving innovation in NLP and other ML solutions, ensuring alignment with Egnyte's business goals.
• Architecting and overseeing scalable, production-ready machine learning systems.
• Providing technical leadership and mentorship to the ML engineering team, fostering growth and collaboration.
• Conducting in-depth research and staying abreast of advancements in machine learning and deep learning technologies.
• Collaborating with cross-functional teams, including Product, to evaluate business requirements and determine optimal ML solutions.
• Designing, deploying, and managing the lifecycle of machine learning models, including retraining and monitoring for continuous improvement.
• Reviewing code, offering best practices, and ensuring the delivery of high-quality solutions.
• Representing Egnyte's technical excellence through publications, presentations, and participation in industry events.

YOUR QUALIFICATIONS:

• 6+ yrs of proven expertise in leading machine learning initiatives, particularly in NLP.
• Extensive experience in creating and deploying machine learning & deep learning models at scale in a SaaS or Cloud environment.
• Demonstrated ability to define and execute technical strategy for ML projects.
• Advanced knowledge of ML frameworks, such as PyTorch and TensorFlow/Keras.
• Proficiency in tools like HuggingFace libraries (transformers and tokenizers) or Fairseq.
• Expertise in Python, Docker, Kubernetes, and Helm.
• Excellent communication skills, particularly in mentoring, knowledge sharing, and cross-team collaboration.
• Strong experience in managing large-scale datasets and distributed computing environments, with a preference for Google Cloud Platform expertise

What we offer:

• Opportunity to work on cutting-edge machine learning projects at scale.
• Leadership role in a growing, innovative AI/ML team.
• Support for continued learning, certifications, and professional growth

Bonus points:

• Proficiency in additional programming languages such as Java, Scala, or Go.
• Familiarity with tools and frameworks like Kubeflow and OpenCV.
• Deep understanding of advanced analytical modeling and statistical forecasting techniques.
• Demonstrated expertise with transformer-based architectures (e.g., BERT, GPT).
• Experience publishing and presenting complex technical work to a broader audience.

COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION:

At Egnyte, we celebrate our differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be.

About the Company -

At Dark Matter Technologies, we're at the forefront of a tech-driven revolution in loan origination. Our commitment to cutting-edge AI and origination technology solutions are reshaping the industry landscape, illuminating a path towards seamless, efficient, and automated experiences.

About the Role -

We are seeking a highly skilled and experienced Senior Data Scientist to join our team.

someone who can build machine learning models and is experienced with using different algorithms for regression, prediction, deep learning, etc. Someone who can be self-sufficient in identifying data sources, analyzing data, and write machine code with python (or Azure ML) and create models.

Job Location: Hyderabad and Bhubaneswar

Responsibilities -

• Selecting features, building, and optimizing classifiers using machine learning techniques
• Hypothesis testing, being able to develop hypothesis and test them with careful experiments
• Experience in implementing Predictive modelling
• Collaborate with cross-functional teams (data engineers, front-end developers, security specialists) to integrate AI models into business solutions.
• Conducts research and experiments to improve AI models and algorithms. Stays updated with the latest AI/ML technologies and trends.
• Implements and deploys AI models using cloud AI services.
• Ensures the quality and scalability of AI solutions

Required Skills

• At least 10 years- experience in Predictive Analytics and Data Mining with hands-on experience in the following areas
• Linear Regression
• Classification Techniques
• Logistic Regression
• Discriminant Analysis
• Unsupervised Learning techniques like k-means/hierarchical clustering
• Feature reduction methods like PCA, SVD

Experience in Optimization methods

• Experience with working in R/Python, T-SQL etc, and graph-based models
• Must have hands on development experience with Python
• Proven experience as a Data Scientist and machine learning model builder
• Understanding of Azure Machine Learning and other Azure AI tools. Proficiency in data modelling and design, including SQL development and
• Develop and deploy machine learning models for key use cases, including regression, predictive analytics, ranking systems, and trend forecasting. Hands-on implementing various machine learning algorithms such as linear regression, deep learning using neural networks, logistic regression, decision trees, and clustering algorithms.
• Perform advanced feature engineering to optimize models and extract meaningful patterns from raw data.
• Work with large-scale datasets, ensuring efficiency and scalability in data processing and analysis
• Collaborate with stakeholders to understand business challenges and design data science solutions that meet organizational needs.
• Strong understanding of statistical analysis and machine learning algorithms.
• Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.
• Present analytical findings and business insights to project managers, stakeholders, and senior leadership and keep abreast of new statistical / machine learning techniques and implement them as appropriate to improve predictive performance.
• Excellent problem-solving skills and ability to work independently as well as part of a team.
• Strong communication skills, both written and verbal, with the ability to communicate complex technical concepts to non-technical stakeholders.

Preferred Skills

• exposure to machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Leverage Azure Machine Learning to manage data pipelines, experiments, and deployments.
• exposure to implementing end-to-end AI solutions using Azure AI services and Azure Cognitive Services.
• Certification in Microsoft Azure AI relative to Azure Machine Learning
• Expert database knowledge in SQL
• Proficiency in Azure Data Services (Data Factory, Synapse Analytics).

Job Description:

This is a very inspiring role in Networks Digitization team where you will use your knowledge and/or experience in Data Science methodologies and apply them to develop analytics based solutions that produce telecom Networks and customer experience use cases as well as quantitative and qualitative business insights. You will work in a highly collaborative environment where you communicate and plan tasks and ideas.

Responsibilities and Duties:

1. Responsible for developing scientific methods, processes, and systems to extract knowledge or insights to drive the future of applied analytics in Networks.

2. Mine and analyze data from company databases to drive optimization and improvement of product development and business strategies.

3. Assess the effectiveness of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to data sets.

4. Use predictive modeling to enhance Network experience customer experiences, revenue generation and other business outcomes.

5. Must be able to communicate effectively and have detailed knowledge of data preparation and cleaning, algorithm selection & design, results analysis, industrialization.

6. Work with stakeholders to understand business requirements and processes for projects so implementation can be done without delays.

7. Work with partners as necessary to integrate systems and data quickly and effectively, regardless of technical challenges or business environments

Qualifications and Skills:

1. Solid understanding in Statistics, e.g., hypothesis formulation, hypothesis testing, descriptive analysis and data exploration.

2. Expertise in Machine Learning, e.g., linear/logistics regression discriminant analysis, bagging, random forest, Bayesian model, SVM, neural networks, ANN ,RNN ,CNN, GEN AI, etc.

3. Good understanding of RAG implementation , LLMs , Fast APIs

4. Strong programming skills in various languages (Python, Scala, R, Pyspark )

5. Strong ambition to learn and implement current state of the art machine learning frameworks such as Scikit- Learn, TensorFlow, and Spark.

6. Familiarity with Linux/OS X command line, version control software (git).

7. Familiarity in programming or scripting to enable ETL development

8. Familiarity with relational databases and SQL .

Academic Qualifications

Masters or equivalent advanced degree in Computer Science, Computer Engineering, Statistics, Mathematics or Related technical discipline.

Pyspark , AI , ML , DL , GEN AI , RAG etc

General Information

Role Title: ML Ops Engineer

Job Location: Bengaluru (Hybrid)

About Fulfillment IQ (FIQ)

At Fulfillment IQ, we are revolutionizing the way companies approach supply chain and logistics. We're an award-winning supply chain tech company, specializing in providing solutions to D2C brands, retailers, and 3PLs. Our dedicated team of supply chain experts, engineers, developers, and subject matter experts help address logistics challenges from software development to supply chain tech implementations.

If you are passionate about supply chain technology and thrive in a challenging environment, we have the perfect opportunity for you to shine and make a difference. We're expanding our team and seeking individuals eager to contribute to a transformative industry, collaborate with top experts, and have a hands-on role in shaping the future of supply chain processes.

Join us now and be a part of our rapidly growing company that's making waves in the supply chain industry.

Position Summary

We are looking for an MLOps Engineer to join our team and help us scale our machine learning products from prototype to production. You will work closely with data scientists, software engineers, and DevOps teams to design, build, and maintain robust, scalable, and automated ML pipelines and infrastructure.

Main Responsibilities

• Build and maintain ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment
• Deploy machine learning models to production using containerization tools like Docker and orchestration systems like Kubernetes
• Set up continuous integration and continuous deployment (CI/CD) pipelines for ML workflows
• Monitor model performance (accuracy, drift, latency) and system health; implement alerts and automated retraining when needed
• Collaborate with data scientists to ensure models are reproducible, version-controlled, and production-ready
• Optimize resource usage (compute, storage, GPUs) and ensure cost-efficient infrastructure on cloud platforms (AWS, GCP, Azure)
• Develop and maintain model governance, including audit trails, explainability, and compliance

Experience and Qualifications

• Bachelor's or master's degree in computer science, Engineering, Data Science, or a related field
• 4-7 years of experience in MLOps, machine learning engineering, or related fields
• Strong programming skills in Python; familiarity with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
• Experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools (Terraform, CloudFormation)
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes)
• Familiarity with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions)
• Understanding of machine learning lifecycle, model monitoring, and data pipelines (Airflow, Kubeflow, MLflow)
• Strong problem-solving skills and the ability to work in a cross-functional team.

Nice-to-Have

• Experience with model explainability and governance tools
• Knowledge of data engineering (Spark, Kafka)
• Familiarity with distributed training, GPUs, and optimization techniques

Why You'll Love Working Here

• Innovative Environment: We are at the forefront of innovation, providing you with opportunities to work on cutting-edge projects that have a global impact.
• Career Growth: We believe in your potential and offer numerous training and development programs to accelerate your career growth.
• Work-Life Balance: We offer flexible working hours, hybrid/remote work options, and a focus on wellness to ensure our team members maintain a healthy balance.
• Diversity & Inclusion: We are committed to creating an inclusive work environment where diverse voices are not just heard but empowered.
• Collaborative Culture: Work with a supportive and talented team, where every opinion is valued, and success is celebrated collectively.
• Corporate events: Annual gathering for gelling up with team from diverse city/state/country with sightseeing and lot more engagement activity and thrill.

Perks and Benefits

• Comprehensive health insurance coverage for employees & their family.
• Generous paid time off, including vacation, holidays, and sick leave.
• Flexible work schedules
• Employee wellness program.
• Opportunities for career development.
• Business/client travel reimbursement, Internet reimbursement, Workstation equipment's
• Sponsored visa to USA (Depends on performance, Client and project needs and management decision)
• Celebrating your work anniversary with Amazon or Sodexo voucher
• Employee Stock options
• Retirement saving plan

FIQ Culture

Fulfillment IQ is a company that values its people, and we work together as a team

while being a remote company. Fulfillment IQ is an equal opportunity employer. We

celebrate diversity and are committed to creating an inclusive environment for all

employees.

To know more about jump on below link

Website:

LinkedIn Page:

Hear us on:

Subscribe us on:

About Netradyne:

Founded in 2015, Netradyne is a technology company that leverages expertise in Artificial Intelligence, Deep Learning, and Edge Computing to bring transformational solutions to the transportation industry. Netradyne's technology is already deployed in thousands of vehicles; and our customers drive everything from passenger cars to semi-trailers on interstates, suburban roads, rural highways-even off-road.

Netradyne is looking for talented engineers to join our Analytics team comprised of graduates from IITs, IISC, Stanford, UIUC, UCSD etc. We build cutting edge AI solutions to enable drivers and fleets realize unsafe driving scenarios in real-time to prevent accidents from happening and reduce fatalities/injuries.

Job Title: Staff Data Engineer - ML

Experience: 5-8 years

Role and Responsibilities:

You will be embedded within a team of machine learning engineers and data scientists; responsible for building and productizing generative AI and deep learning solutions. You will:

• Design, develop and deploy production ready scalable solutions that utilizes GenAI, Traditional ML models, Data science and ETL pipelines
• Collaborate with cross-functional teams to integrate AI-driven solutions into business operations.
• Build and enhance frameworks for automation, data processing, and model deployment.
• Utilize Gen-AI tools and workflows to improve the efficiency and effectiveness of AI solutions.
• Conduct research and stay updated with the latest advancements in generative AI and related technologies.
• Deliver key product features within cloud analytics.

Requirements:

• B. Tech, M. Tech or PhD in Computer Science, Data Science, Electrical Engineering, Statistics, Maths, Operations Research or related domain.
• Strong programming skills in Python, SQL and solid fundamentals in computer science, particularly in algorithms, data structures, and OOP.
• Experience with building end-to-end solutions on AWS cloud infra.
• Good understanding of internals and schema design for various data stores (RDBMS, Vector databases and NoSQL).
• Experience with Gen-AI tools and workflows, and large language models (LLMs).
• Experience with cloud platforms and deploying models at scale.
• Strong analytical and problem-solving skills with a keen attention to detail.
• Strong knowledge of statistics, probability, and estimation theory.

Desired Skills:

• Familiarity with frameworks such as PyTorch, TensorFlow and Hugging Face.
• Experience with data visualization tools like Tableau, Graphana, Plotly-Dash.
• Exposure to AWS services like Kinesis, SQS, EKS, ASG, lambda etc.
• Expertise in at least one popular Python web-framework (like FastAPI, Django or Flask).
• Exposure to quick prototyping using Streamlit, Gradio, Dash etc.
• Exposure to Big Data processing (Snowflake, Redshift, HDFS, EMR)

Senior Software Engineer, Machine Learning

About the role

Our Client is seeking a Senior Software Engineer, Machine Learning, who is a smart, creative, and curious analytical thinker with a passion for working hands-on with big data. Our Clients are on a mission to empower healthcare through the measurement and prediction of patient outcomes. The team focuses on extracting critical clinical information from unstructured data, such as clinical notes. By joining the team, you will play an essential role in unlocking valuable insights for analytical studies and cohort analyses.

The team is responsible for maintaining and evolving multiple big data pipelines designed to extract clinical outputs from medical notes efficiently. We value an experimental mindset that embraces failing fast, iterating quickly to refine solutions, and recognizing the right balance between generalization and specificity to avoid premature optimization.

What You'll Do

Build, maintain, and deploy efficient pipelines to process large amounts of unstructured data

Craft scalable software and tools using software engineering practices

Use LLM-based models to extract actionable clinical information

Translate research project requirements into data specifications

Collaborate openly with software engineers, product managers, and clinical teams to deliver high-quality data and software

Regularly share progress, including setbacks, with your teammates to foster open communication.

Recognize when solutions and systems should be generalized and when it is prudent to focus on specific needs, avoiding premature optimization

What Experience You'll Bring

5-8 years of experience

Expertise in Python and SQL

Experience working with large-scale healthcare data

Hands-on experience with applying and deploying Machine Learning models

Strong desire to enhance and optimize processes

Deep curiosity

Desire to make processes better and more efficient

Extreme comfort clarifying and pushing back against requirements

Excellent communication skills, both verbal and written, for technical and non-technical audiences

Strong commitment to high-quality data and code

What's Nice to Have

Experience with dbt

Hands-on experience with Large Language Models (LLMs)

Experience with LLM APIs and ecosystems

e.g., openai api, langchain

If you're excited about this role but your past experience doesn't align perfectly with every qualification, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

Email -

Project Role: Sr Machine Learning Engineer

Work Experience: 4 to 8 Years

Work location: Bengaluru/Pune/Gurgaon

Work Mode: Hybrid

Must Have Skills: Machine Learning, NLP, Python, LLM

Job Overview:

Develop AIML models/algorithms/processes to address pharma/healthcare applications and innovative products upon completion of prototypes followed by the building of production grade algorithms/automation engines for client deliverables.

Job Responsibility:

• Assists with the ongoing development and implementation of an enterprise architecture.
• Builds effective business relationships with business line managers and provides technical and system expertise as input to product concepts.
• May assist product development management to define IT strategic direction and assists in the mapping of projects to that strategic direction whilst ensuring product capabilities
• Participates in cross-functional product development teams, may also act as a consultant to provide system and technical advice.
• Participates in R&D projects and may run those projects in compliance with standard project management practices.

Technical Skills:

• Experience on NLP, Machine Learning and Deep learning
• Experience working on Python
• Extensively work on NLP applications, ability to work on Machine learning model, Deep learning development
• Knowledge of LLMs, fine tuning and deployment
• Experience in annotated datasets for Supervised Learning methods and correction

.Educational Qualification: BTech/BCA/BSc/MTech/MCA/MSc