Find Your Dream Machine Learning Job in India

What's the role?

If you are looking for an opportunity to solve deep technical problems, build innovative solutions, and work with top-notch developers, AGDATA has the role for you.

You must be able to look at the big picture from both business and technology perspective, possess strong analytical, design, and problem-solving skills.

You are not afraid of ambiguity, dealing with nebulous requirements, and get excited about difficult challenges.

In this role, you will

• Design, build, and deploy scalable machine learning models from prototype to production.
• Analyze large volumes of structured and unstructured data to identify patterns, trends, and anomalies.
• Build and maintain robust data pipelines, including data cleaning, transformation, and aggregation.
• Store and manage model outputs in SQL databases and ensure integration with downstream reporting systems.
• Interpret and communicate findings using statistical and analytical techniques.
• Collaborate with cross-functional teams to understand project goals and deliver data-driven solutions.
• Lead end-to-end ML lifecycle: from model development to deployment, testing, tuning, and monitoring.
• Participate in proof of concepts (POCs) and evaluate tools and frameworks for use in AI/ML projects.
• Mentor junior engineers and guide teams on best practices with AI/ML tools and processes.
• Contribute to building internal capabilities and processes for scaling ML efforts across the organization.

Required Skills & Experience:

• Bachelor's or higher degree in computer science, Data Science, Statistics, Mathematics, or a related field.
• 12+ years of experience with at least 6+ years in Data Science / Machine Learning roles.
• Strong programming skills in R and Python.
• Experience with fastai, PyTorch, TensorFlow, Scikit-learn, and Keras.
• Proficiency in SQL and working knowledge of relational databases such as PostgreSQL or MySQL.
• Hands-on experience with data manipulation libraries and frameworks: Pandas, NumPy, Tidyverse, ggplot2, dplyr, data.table etc.
• Experience working with cloud platforms like AWS, Azure, or Google Cloud, and containerization tools like Docker and Kubernetes.
• Familiarity with Infrastructure as Code tools such as Terraform, Pulumi, or CloudFormation.
• Exposure to NoSQL databases, REST API development, and automated model deployment workflows.
• Practical understanding of NLP, computer vision, or predictive modeling.
• Strong problem-solving and communication skills.

Nice to Have:

• Experience with tools like H2O, XGBoost, LightGBM.
• Knowledge of emerging areas like IoT, blockchain, or quantum computing in the context of data science.
• Proven track record of delivering ML solutions in production environments.

How AGDATA will support you:

Supporting your health & well-being:

• Comprehensive medical coverage - up to INR 7.5 lakh for employee and dependents, including parents.
• OPD benefit - coverage of up to INR 15 thousand covering expenses across specialties.
• Paternity leaves up to 14 working days with the option to split leave.

Emphasizing work life balance: Flexible hybrid work policy

Experiencing a work culture that promotes from within: In 2023, 13% of our associates were promoted internally.

Being comfortable in the office: Coming into our brand-new office space? Free snacks and top-class facilities will be available for you.

Website

Machine Leaning Engineer

Experience-6+Years

Notice period-max 15 days

Location -Pune/Remote

Job Summary:

Job Overview

Machine Learning Engineer (Python, AWS)

We are seeking an experienced Machine Learning Engineer with 5+ years of hands-on experience in developing and deploying ML solutions. The ideal candidate will have strong Python programming skills and a proven track record working with AWS services for machine learning.

Responsibilities:

• Design, develop, and deploy scalable machine learning models.
• Implement and optimize ML algorithms using Python.
• Leverage AWS services (e.g., Sagemaker, EC2, S3, Lambda) for ML model training, deployment, and monitoring.
• Collaborate with data scientists and other engineers to bring ML solutions to production.
• Ensure the performance, reliability, and scalability of ML systems.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of professional experience as a Machine Learning Engineer.
• Expertise in Python programming for machine learning.
• Strong experience with AWS services for ML (SageMaker, EC2, S3, Lambda, etc.).
• Solid understanding of machine learning algorithms and principles.
• Experience with MLOps practices is a plus.

About Trademo

Trademo is a Global Supply Chain Intelligence SaaS Company, headquartered in Palo-Alto, US. Trademo collects public and private data on global trade transactions, sanctioned parties, trade tariffs, ESG and other events using its proprietary algorithms.Trademo analyzes and performs advanced data processing on billions of data points (50Tb+) using technologies like Graph Databases, Vector Databases, ElasticSearch, MongoDB, NLP and Machine Learning (LLMs) to build end-to-end visibility on Global Supply Chains. Trademo's vision is to build a single truth on global supply chains to different stakeholders in global supply chains - discover new commerce opportunities, ensure compliance with trade regulations, and automation for border security.

Trademo stands out as one of the rarest Indian SaaS startups to secure 12.5 mn in seed funding. Founded by Shalabh Singhal, who is a third-time tech entrepreneur and an alumni of IIT BHU, CFA Institute USA, and Stanford GSB SEED. Our Trademo is backed by a remarkable team of leaders and entrepreneurs like Amit Singhal (Former Head of Search at Google), Sridhar Ramaswamy (CEO, Snowflake), Neeraj Arora (MD, General Catalyst & Former CBO, Whatsapp Group.

What you will be doing?

• Define and execute Trademo's AI roadmap across five core products
• Architect and implement GenAI pipelines for document intelligence, HS code classification, sanctions screening, and supply chain mapping
• Lead R&D on LLM-based tools (e.g., RAG, prompt optimization, fine-tuning, agents)
• Work hands-on with engineers to build and scale production-ready models
• Mentor and manage a small team of AI/ML engineers and interns
• Collaborate cross-functionally with product managers, designers, and compliance SMEs
• Stay ahead of trends in GenAI, transformers, open-source LLMs, and model orchestration tools

Desired Profile

• 4-6 years of experience in applied AI/ML, with at least 3 years focused on LLMs/GenAI
• Strong background in machine learning, NLP, and Python-based AI tooling (LangChain, HuggingFace, etc.)
• Experience deploying models in production within SaaS or platform environments
• Ability to architect, prototype, and optimize AI systems end-to-end
• Prior experience managing small teams or mentoring engineers
• Exposure to compliance, fintech, logistics, or enterprise SaaS is a plus.

Job Summary:

We are looking for a Machine Learning Engineer with strong expertise in core statistical modeling and traditional machine learning techniques. The ideal candidate will have a solid foundation in regression model development , feature engineering , and statistical analysis , along with hands-on experience deploying models in production environments using AWS services . While experience with Amazon Bedrock and generative AI is a plus, this role is primarily focused on traditional ML - not data science research or LLM experimentation.

Key Responsibilities:

• Design and implement statistical and ML models (e.g., linear regression, logistic regression, decision trees, ensemble methods) for business-critical applications.

• Perform exploratory data analysis, feature engineering , and data preprocessing using best statistical practices.

• Build and deploy scalable ML pipelines using AWS-native services such as SageMaker, Lambda, S3, and API Gateway.

• Ensure robust model evaluation, testing, and performance tuning using cross-validation, ROC/AUC, and other statistical metrics.

• Collaborate with software/data engineering teams to integrate models into production systems.

• Maintain clean, efficient, and well-documented ML code with CI/CD and MLOps best practices.

• Optional Contribute to GenAI use cases if relevant, leveraging Amazon Bedrock or similar platforms for LLM-powered components.

Required Skills & Qualifications:

• 6+ years of hands-on ML engineering experience , preferably in production environments.

• Proven expertise in statistical modeling and regression analysis .

Hands-on experience with Amazon Bedrock.

• Strong programming skills in Python with frameworks such as Scikit-learn , XGBoost , TensorFlow , or PyTorch .

• Experience with AWS ML services : SageMaker, Lambda, S3, API Gateway, etc.

• Solid understanding of statistical techniques such as hypothesis testing, sampling, time-series forecasting, PCA, etc.

• Exposure to MLOps workflows , including model monitoring, versioning, and automation pipelines.

• Excellent problem-solving, debugging, and communication skills.

Nice to Have:

• Experience with Prompt engineering, or LLM-based architectures .

• Familiarity with RAG (Retrieval-Augmented Generation) or vector databases like Pinecone/FAISS.

• AWS ML Specialty Certification or equivalent.

We are looking for a visionary and technically skilled Lead AI Engineer - Machine Learning

to spearhead the design, development, and deployment of advanced machine learning solutions.

In this leadership role, you will guide a team of AI/ML engineers, contribute hands-on to critical

technical challenges, and collaborate with cross-functional teams to deliver impactful AI

products. This role is ideal for someone who thrives at the intersection of innovation, engineering

rigor, and business value.

Key Responsibilities

Technical Leadership: Lead the architecture, development, and deployment of machine

learning models and AI systems across a range of use cases.

Model Development: Design, train, and optimize supervised, unsupervised, and deep

learning models using frameworks like PyTorch, TensorFlow, and XGBoost.

Mentorship: Coach and mentor a team of ML engineers and data scientists; foster a

culture of innovation, ownership, and continuous learning.

Project Management: Drive planning, execution, and delivery of AI/ML projects,

ensuring alignment with business objectives and technical feasibility.

System Design: Architect scalable, secure, and high-performance ML pipelines and

services using cloud-native tools and MLOps best practices.

Collaboration: Work closely with product managers, data engineers, and DevOps teams

to translate business problems into AI-driven solutions.

Code Quality & Governance: Establish standards for model quality, reproducibility,

documentation, versioning, and monitoring.

Innovation: Stay current with research and industry trends in ML/AI, evaluate new tools,

and introduce state-of-the-art solutions where applicable.

Required Skills and Experience

Education: Bachelor's or Master's in Computer Science, Machine Learning, Data

Science, or related technical field

Experience: 6-10+ years of experience in software engineering or AI/ML, with at least

2+ years in a technical leadership role

Technical Expertise:

o Strong programming skills in Python and experience with ML libraries such as

Scikit-learn, TensorFlow, PyTorch, Hugging Face

o Deep understanding of ML fundamentals: feature engineering, model evaluation,

optimization, and deployment

o Proficiency in designing and building data pipelines, real-time processing, and

model inference systems

o Experience with cloud platforms (AWS, GCP, or Azure), containerization

(Docker, Kubernetes), and CI/CD pipelines

o Familiarity with MLOps tools (e.g., MLflow, DVC, Airflow, SageMaker) and

vector databases (e.g., FAISS, Pinecone)

Preferred Qualifications

Hands-on experience with LLMs, RAG pipelines, or generative AI applications

Familiarity with agentic AI frameworks (LangChain, CrewAI, AutoGPT)

Domain expertise in fintech, healthtech, HR tech, or industrial automation

Contributions to open-source AI/ML projects or published research

Knowledge of responsible AI practices, explainability (XAI), and model governance

Soft Skills

Strong leadership and team-building skills

Clear and persuasive communication with both technical and non-technical stakeholders

Strategic thinker with attention to detail and a bias for action

About OrbitShift

OrbitShift is an AI-led SaaS Product transforming enterprise consultative technology sales. With a top-notch team of leaders from Amazon, McKinsey, IIT, Stanford, we've raised $8.5M from marquee investors like PeakXV (Sequoia Surge) & Stellaris Venture Partners. We're currently expanding our teams across India & USA.

About the role

We're looking for a rockstar ML Engineer looking to join a dynamic, fast-paced environment, work closely with cross-functional teams, and hands-on experience in Generative AI and a proven track record of building and deploying scalable Generative AI products.

Responsibilities

• Craft smart, scalable NLP solutions using cutting-edge Gen AI techniques
• Lead full-cycle ML projects-from problem definition to live deployment
• Dive deep into LLMs (like Mixtral, Llama etc.) and fine-tune them for business applications
• Build advanced AI agents (information extraction, summarization, chat interfaces)
• Work hand-in-hand with product managers, designers, and engineers to turn ideas into magical AI features
• Bring MLOps best practices to life - ensuring performance, monitoring, and retraining are all seamless
• Continuously experiment, learn, and improve - because that's what great AI teams do

Requirements

• Bachelor's degree in Computer Science, Engineering, IT, or a related field.
• 4+ years of relevant ML experience with strong exposure to Gen AI
• Hands-on experience with HuggingFace, Langchain, OpenAI, or similar ecosystems
• Proven experience with Retrieval Augmented Generation (RAG) and LLM fine-tuning
• Solid foundation in NLP, deep learning (Transformers, embeddings etc.)
• Proficient with one of the programming languages like Python, Js etc.
• Experience with Agent building frameworks like Crew, Autogen or Lang Graph would be a plus
• Cloud deployment experience (AWS, Azure, or GCP)
• Strong communicator-able to explain complex tech in simple terms

Why choose OrbitShift

• We're a lean team with a flat hierarchy
• Now is the best time to join as we've already cracked the code on a product that customers love, but are early-stage enough offering unparalleled learning opportunities
• High ownership & transparency
• Fast-tracked growth and career progression
• You get to build for and sell to an international enterprise customer base
• Hybrid work setup & flexible work hours
• Competitive salary & equity
• Health Insurance for employees & their families
• Professional Development allowance for online courses

OrbitShift is an equal-opportunity employer. Candidates will not be discriminated against based on race, ethnicity, color, religion, caste, sex, gender identity, sexual orientation, national origin, veteran, or disability status.

Machine Learning Engineer (With the focus of AI SaaS Development)

Job Type: Part-time (Project based)

Location: Fully Remote

Compensation: Market competitive

Who Can Apply: Fresh graduate or 6 months of experience

Overview:

We are seeking a talented and driven Machine Learning (ML) Engineer focused on AI SaaS product development. Candidates with 6 months or 1 year of hands-on experience or fresh graduates are welcome to apply. This role involves building cutting-edge AI agents, optimizing end-to-end solutions, and collaborating with international clients (primarily US-based). You will be responsible for developing scalable and efficient AI SaaS products from inception to deployment.

Key Responsibilities:

Build AI agents using frameworks like LangChain, AutoGen, and LangGraph.

Develop frontends using Next.js and backends using FastAPI or Django.

Create, deploy, and fine-tune AI solutions, including LLMs and RAG (Retrieval-Augmented Generation) systems, optimizing them for production.

Work with vector databases and handle AI model fine-tuning and deployment (AWS, GCP, Hugging Face).

Implement CI/CD pipelines, ensuring seamless deployment and updates.

Collaborate with international clients to deliver high-quality AI SaaS products that meet their needs.

Ensure solutions are scalable, secure, and optimized for performance.

Provide support for maintaining and enhancing existing AI solutions.

Required Skills and Qualifications:

Fresh graduate or 6+ months of experience in AI/ML.

Proficiency in Python, AI/ML concepts, and frameworks such as LangChain and AutoGen.

Experience with AWS, GCP, Hugging Face, and deploying models at scale.

Strong knowledge of CI/CD, Git, and automation pipelines.

Familiarity with both frontend development (Next.js) and backend frameworks (FastAPI/Django).

Solid understanding of LLMs, fine-tuning, vector databases, and RAG systems.

Ability to design and build AI products from concept to production-ready solutions.

Preferred Qualifications:

Experience working in a fully remote environment with international clients.

Strong problem-solving skills and the ability to work independently.

Excellent communication skills and a collaborative mindset.

Knowledge of NLP, machine learning pipelines, and advanced AI technologies is a plus.

Direct apply or send your latest resume to:

AI/ML ENGINEER

Who We Are?

Cleantech Industry Resources accelerates United States solar, battery storage and EV projects by providing turnkey development as a service including 100% internal systems engineering. The company deploys a leading team that spun out of the largest solar power producer in the world. This team operates within a sophisticated suite of software to support projects from land origination, through to commercial operation.

Location

Chennai

What We Offer

• Opportunity to join a top-notch, collaborative team of professionals
• Fantastic team environment and collaborative culture
• Professional development opportunities to grow into an industry leader
• Medical Insurance for the employee and family
• Spot Recognition bonus for exceptional performance
• Long Term Incentive policy
• Regular team outings, events, and activities to foster a positive work environment

Our Commitment to Diversity

At CIR, we are dedicated to nurturing a diverse and equitable workforce that truly reflects our community. We deeply value each person's unique perspective, skills, and experiences. CIR embraces all individuals, regardless of race, religion, sexual orientation, gender identity, age, or nationality. We are steadfast in our commitment to fostering a just and inclusive world through intentional policies and actions. Your individuality enriches our collective strength, and we strive to ensure everyone feels respected, valued, and empowered.

Position Summary

We are looking for an AI/ML Engineer to build and optimize machine learning models for GIS-based spatial analysis and data-driven decision-making. This role involves working on geospatial AI models, data pipelines, and Retrieval-Augmented Generation (RAG)-based applications for zoning, county sentiment analysis, and regulatory insights. The engineer will also work closely with the data team, leading efforts in data curation and building robust data pipelines to collect, preprocess, and analyse extensive datasets from various geospatial and regulatory sources to generate automated reports and insights.

Core Responsibilities

Machine Learning for GIS & Spatial Analysis:

• Develop and deploy ML models for geospatial data processing, forecasting, and automated GIS insights.
• Work with large-scale geospatial datasets (e.g., satellite imagery, shapefiles, raster/vector data).
• Create AI models for land classification, feature detection, and geospatial pattern analysis.
• Optimize spatial data pipelines and build predictive models for environmental and energy sector applications.

Retrieval-Augmented Generation (RAG) & NLP Development:

• Develop RAG-based AI applications to extract insights from zoning, permitting, and regulatory documents.
• Build LLM-based applications for zoning law interpretation, county sentiment analysis, and compliance predictions.
• Implement document retrieval and summarization techniques for legal, policy, and energy development reports.

Data Engineering & Pipeline Development:

• Lead the creation of ETL pipelines to collect and preprocess geospatial data for ML model training.
• Work with PostGIS, PostgreSQL, and cloud storage to manage structured and unstructured data.
• Collaborate with the data team to design and implement efficient data processing and storage solutions.

AI Model Optimization & Deployment:

• Fine-tune LLMs for domain-specific applications in renewable energy and urban planning.
• Deploy AI models using cloud-based MLOps frameworks (AWS, GCP, Azure).
• Optimize ML model inference for real-time GIS applications and geospatial data analysis.

Collaboration & Continuous Improvement:

• Work with cross-functional teams to ensure seamless AI integration with existing business processes.
• Engage in knowledge sharing and mentoring within the company.
• Stay updated with latest advancements in AI, GIS, and NLP to improve existing models and solutions.

Education Requirements

Master's in Computer Science, Data Science, Machine Learning, Geostatistics, or related fields.

Technical Skills and Experience

Software Proficiency:

• Programming: Python (TensorFlow, PyTorch, scikit-learn, pandas, NumPy), SQL.
• Machine Learning & AI: Deep learning, NLP, retrieval-based AI, geospatial AI, predictive modeling.
• GIS & Spatial Data Processing: Experience with PostGIS, GDAL, GeoPandas, QGIS, Google Earth Engine.
• LLM & RAG Development: Experience in fine-tuning LLMs, retrieval models, vector databases (FAISS, Weaviate).
• Cloud & MLOps: AWS/GCP/Azure, Docker, Kubernetes, MLflow, FastAPI.
• Big Data Processing: Experience with large-scale data mining, data annotation, and knowledge graph techniques.
• Database & Storage: PostgreSQL, NoSQL, vector databases, cloud storage solutions.
• Communication: Strong ability to explain complex AI/ML concepts to non-technical stakeholders.

Project Management:

• Design experience in projects from conception to implementation.
• Ability to coordinate with other engineers and stakeholders.

Renewable Energy Systems:

• Understanding of solar energy systems and their integration into existing infrastructure

Experience

• 2-4 years of experience
• Experience in developing AI for energy sector, urban planning, or environmental analysis.
• Strong understanding of potential prediction, zoning laws, and regulatory compliance AI applications.
• Familiarity with spatiotemporal ML models and satellite-based geospatial analytics.

Psychosocial Skills /Human Skills/Behavioural Skills

• Strong analytical, organizational, and problem-solving skills.
• Management experience a plus.
• Must be a go-getter with an enterprising attitude
• A self-starter, able to demonstrate high levels of initiative and motivation
• Entrepreneurial mindset with the ability to take ideas and run with them from concept to conclusion.
• Technical understanding of clean energy business processes
• Exceptional verbal and writing communication skills with superiors, peers, partners, and other stakeholders.
• Excellent interpersonal skills while managing multiple priorities in a fast-paced and ever-changing environment.

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The physical demands of this job require an individual to be able to work at a computer for most of the day, be able to participate in conference calls and travel to team retreats on a time-to-time basis. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Work Conditions

The work environment is usually quiet (normal city traffic noises are common), a blend of artificial and natural light, temperate and generally supports a collaborative work environment. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Equal Opportunity Employer

At Cleantech Industry Resources, we embrace diversity and uphold a strong dedication to establishing an all-encompassing atmosphere for both our staff and associates. Our choices in employment are free from any bias related to race, creed, nationality, ethnicity, gender, sexual orientation, gender identity, gender expression, age, physical limitations, veteran status, or any other legally safeguarded attributes.

Being an integral part of Cleantech Industry Resources means you can expect to be immersed in a realm of professional possibilities within a culture that nurtures teamwork, adaptability, and the embracing of all.

Glance - An InMobi Group Company Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance's 'smart lock screen' inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete.

Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit nostra.gg, and

What should you know about joining Glance? :

At Glance, we walk the talk - free yourself, dream big, and chase your passion! On joining, you'll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups. Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences. While you work, we'll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids - even the furry ones - to the office!

What you will be doing? :

Glance is looking for a Machine Learning Engineer. As an ML engineer you will be responsible for contributing to the design, development, deployment, testing, maintenance and enhancement of ML software solutions. You will work closely with data scientists to collaborate and support the development of ML data pipelines, platforms and infrastructure.

Day-to-day activities include:

• architecting and implementing end-to-end solutions for accelerating experimentation and model building

• creation of microservices and APIs for serving ML models and ML services

• designing and implementing potential products and proof-of-concepts

• working closely with engineering, product, and newsroom teams to define and deploy new ML / AI products

• exploring and onboarding new platforms, technologies and algorithms

• managing project priorities, deadlines and deliverables. We are looking for candidates with an enthusiasm for tackling audacious challenges, the ability to take ownership of end-to-end solutions, and a passion for elegance in deep problem solving.

Preferred Qualifications:

• Five+ years' experience working in a ML Engineering role with proven track record of delivering high-impact ML solutions.

• Bachelor's degree, Master's or PhD in computer science, Mathematics, Statistics, or other analytical fields

• Demonstrated ability to own end-to-end project delivery while maintaining transparent communication

• Hands-on experience and strong theoretical understanding of Recommender Systems.

• Experience working with Python, Golang, Spark or other open-source software with data science libraries

• Strong experience in advanced math and statistics

• Excellence in technical documentation and project leadership, with proven ability to drive results independently with cross-functional teams

• Experience with being actively engaged in data science or other research-oriented position.

About the Job:

• Collaborate with the product team, data scientists and other stakeholders across the company to understand and define business requirements
• Effectively communicate complex technical concepts to both technical and non-technical teams
• Lead end-to-end lifecycle of ML microservices - from planning and design to implementation, deployment, and monitoring - in partnership with fellow ML engineers
• Write clean, efficient, reusable, and maintainable code
• Enhance and take ownership of our current codebases, systems, and workflows
• Drive team productivity and deliver excellence while fostering sustainable development practices
• Guide and mentor other engineers, and promote a culture of continuous learning and growth
• Drive architectural decisions and technical direction while fostering a culture of engineering excellence

About you:

• Bachelor's degree in Computer Science or equivalent
• 4-7+ years of experience in backend engineering
• 3+ years of experience in Python
• Expertise in Flask/FastAPI, APIs, SQL, AWS/GCP, RabbitMQ/Kafka/SQS, Docker and CI/CD practices
• Experience implementing monitoring tools (e.g., Datadog, Grafana) to track latency, errors, and alerts for scalable backend systems
• Proven leadership in planning and implementing medium to large-scale software projects
• Excellent communication and collaboration skills
• Preferred experience in deploying ML models in production
• Startup experience is a plus

What We Do:

At ClearTrail, work is more than 'just a job'. Our calling is to develop solutions that empower those dedicated to keep their people, places and communities safe.

For over 23 years, law enforcement & federal agencies across the globe have trusted ClearTrail as their committed partner in safeguarding nations & enriching lives. We are envisioning the future of intelligence gathering by developing artificial intelligence and machine learning based lawful interception & communication analytics solutions that solve the world's most challenging problems.

Role - ML Engineer (6-10 years' experience) with ML and LLM skill set

Location - Indore, MP, Bangalore

Qualifications:

• Bachelor's degree in computer science & engineering.
• 6-10 years of Proven experience as a Machine Learning Engineer or similar role with LLM skill set
• Sound theoretical and practical knowledge of working with machine learning algorithms and hands-on with LLM applications

Responsibilities:

• Develop end-to-end machine learning pipeline which includes model development, refining, and implementation for variety of analytics problems.
• Communicate results to diverse technical and non-technical audiences.
• Provides LLM expertise to solve problems using state-of-the-art language models and off-the-shelf LLM services, such as OpenAI models etc. Along with knowledge around Retrieval augmented generation and relevant techniques to improve performance & capabilities of LLMs
• Research and Innovation: Stay up to date with the latest advancements in the fields of AI.
• Probem-solving and code debugging skills.
• Hands on practical experience with usage of large language and generative AI models both proprietary and opensource, including transformers and GPT models (preferred)

Mandatory Skills:

• Libraries: Python, Scikit-Learn, PyTorch, LangChain, Transformers
• Techniques: Exploratory Data Analysis, Machine Learning and Neural Networks
• Machine learning model building, Hyperparameter tuning and Model performance metrics and Model Deployment
• Practical knowledge of LLM and its finetuning

Good to Have Skills -

• Deep Learning
• MLOps
• SQL

Company Mission

Leegality is India's first Document Infrastructure Platform - a radical new digital way for businesses to complete paperwork (agreements, forms and other legal documents). Over the last 7 years, Leegality has changed the way 2000+ Businesses do their paperwork from large enterprises like HDFC, SBI Cards, Federal Bank, ICICI Lombard, Axis Finance, Tata Capital etc. to high-growth companies like Razorpay, Rupeek, Cars24, Dunzo etc.

To see our impact on customers click here

Company Environment

Leegality has an Employee Net Promoter Score of 97 - the highest on xto10x's eNPS Survey for Q1 2022. The highest among 60+ notable startups. This makes us, arguably, the most employee-loved startup in the country

Creating a category-defining company - and changing the way businesses perform a critical function like paperwork - requires powerful marketing that resonates with people.

Job Brief:

• As ML Engineer, you will develop solutions to interesting technical problems, explore exciting growth opportunities and have a real impact on our product.
• To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software.

Responsibilities:

• Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
• Transforming data science prototypes and applying appropriate ML algorithms and tools.
• Solving complex problems with multi-layered data sets and optimizing existing machine learning libraries and frameworks.
• Developing ML algorithms to analyze huge volumes of historical data to make predictions.
• Running tests, performing statistical analysis, and interpreting test results.
• Exposure to generative AI (LLM) based ML architectures
• Experienced in working with CNN.
• Knows how to train and fine tune CNN based models.
• Documenting machine learning processes.
• Keeping abreast of developments in machine learning.

Requirements:

• 1+ years of relevant experience in Machine Learning Engineering.
• Advanced proficiency with Python.
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
• In-depth knowledge of mathematics, statistics, and algorithms.
• Superb analytical and problem-solving abilities.
• Great communication and collaboration skills.
• Excellent time management and organizational abilities.

Preferences:

• Start-up experience is good to have.
• Willing to join immediately ideally.

Recruitment Process:

• To effectively evaluate your application, it is important that we get to know you better. It is necessary that you complete the job-based assessment.
• Please answer all questions in the assessment thoroughly.
• You will be shortlisted based on your profile and answers to the job - based assessment.
• On being shortlisted, you would be contacted for the interview process.
• We further have 3 rounds of interviews.
• Your final CTC would be decided on the basis of your skills, experience and final assessment.

Apply directly through our career page:

For more information about us please visit our:

Our Company and Culture:

Our Website:

Our LinkedIn Page: y/

MACHINE-LEARNING ENGINEER

ABOUT US

Datacultr is a global Digital Operating System for Risk Management and Debt Recovery, we drive Collection Efficiencies, Reduce Delinquencies and Non-Performing Loans (NPL's). Datacultr is a Digital-Only provider of Consumer Engagement, Recovery and Collection Solutions, helping Consumer Lending, Retail, Telecom and Fintech Organizations to expand and grow their business in the under-penetrated New to Credit and Thin File Segments.

We are helping millions of new to credit consumers, across emerging markets, access formal credit and begin theirjourney towards financialhealth. We have clients acrossIndia, South Asia, South East Asia, Africa and LATAM.

Datacultr is headquartered in Dubai, with offices in Abu Dhabi, Singapore, Ho Chi Minh City, Nairobi, and Mexico City; and our Development Center is located out of Gurugram, India.

ORGANIZATION'S GROWTH PLAN

Datacultr's vision is to enable convenient financing opportunities for consumers, entrepreneurs and small merchants, helping them combat the Socio-economic problems this segment faces due to restricted access to financing.

We are on a missionto enable 35 million unbanked& under-served people,access financial services by the end of 2026.

Position Overview

We're looking for an experienced Machine Learning Engineer to design, deploy, and scale production-grade ML systems. You'll work on high-impact projects involving deep learning, NLP, and real-time data processing-owning everything from model development to deployment and monitoring while collaborating with cross-functional teams to deliver impactful, production-ready solutions.

Core Responsibilities

• Representation & Embedding Layer
• Evaluate, fine-tune, and deploy multilingual embedding models (e.g., OpenAI text-embedding-3, Sentence-T5, Cohere, or in-house MiniLM) on AWS GPU or serverless endpoints.
• Implement device-level aggregation to produce stable vectors for downstream clustering.
• Cohort Discovery Services
• Build scalable clustering workflows in Spark/Flink or Python on Airflow.
• Serve cluster IDs & metadata via feature store / real-time API for consumption.
• MLOps & Observability
• Own CI/CD for model training & deployment.
• Instrument latency, drift, bias, and cost dashboards; automate rollback policies.
• Experimentation & Optimisation
• Run A/B and multivariate tests comparing embedding cohorts against legacy segmentation; analyse lift in repayment or engagement.
• Iterate on quantisation, distillation, and batching to hit strict cost-latency SLAs.
• Collaboration & Knowledge-sharing
• Work hand-in-hand with Product & Data Strategy to translate cohort insights into actionable product features.

Key Requirements

• 5-8 years of hands-on ML engineering / NLP experience; at least 2 years deploying transformer-based models in production.
• Demonstrated ownership of pipelines processing 100 million events per month.
• Deep proficiency in Python, PyTorch/TensorFlow, Hugging Face ecosystem, and SQL on cloud warehouses.
• Familiar with vector databases and RAG architectures.
• Working knowledge of credit-risk or high-volume messaging platforms is a plus.
• Degree in CS, EE, Statistics, or related;

Tech Stack You'll Drive

• Model & Serving - PyTorch, Hugging Face, Triton, BentoML
• Data & Orchestration - Airflow, Spark/Flink, Kafka
• Vector & Storage - Qdrant/Weaviate, S3/GCS, Parquet/Iceberg
• Cloud & Infra - AWS (EKS, SageMaker)
• Monitoring - Prometheus, Loki, Grafana

What We Offer

• Opportunity to shape the future of unsecured lending in emerging markets
• Competitive compensation package
• Professional development and growth opportunities
• Collaborative, innovation-focused work environment
• Comprehensive health and wellness benefits

Location & Work Model

• Immediate joining possible
• Work From Office only
• Based in Gurugram, Sector 65

Kindly share your updated profile with us at to guide you further with this opportunity.

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Project Description:

We are looking for a Machine Learning (ML) Engineer to help us create artificial intelligence products.

Responsibilities:

I. EDA: Capability to handle and transform data from Snowflake Warehouse and Azure Data Factory

II. ML Models

1. Regression Models - Linear and Logistic Regression, Decision Trees

2. Classification Models - Random Forest, SVM, Gradient Boost etc

4. Clustering Techniques - KNN

III. ML Ops: Setup training & inference pipelines, model registry and deployment in Azure MLOps

Nice to have skills:

1. Deep Learning Models - Tensor Flow and Keras

2. Anomaly Detection Models

3. Associate Rule Mining

4. Azure Dashboard, or PowerBI

Mandatory Skills:

• 5+yrs of relevant experience
• SnowFlake, Warehouses, Event Driven Architecture (EDA), Machine Learning, Azure Data Factory (ADF) Pipeline Full loads and Maintenance Activities

Nice-to-Have Skills:

• Basic knowledge of Cloud Services
• Knowledge of ITIL, Agile methodologies
• Able to work independently and interact with the business community, and L3 team to come up with solutions.

Languages:

• English: B2 Upper Intermediate

About Navi:

Navi is one of the fastest-growing financial services companies in India providing Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. Navi's mission is to deliver digital-first financial products that are simple, accessible, and affordable. Drawing on our in-house AI/ML capabilities, technology, and product expertise, Navi is dedicated to building delightful customer experiences.

Founders: Sachin Bansal & Ankit Agarwal

Know what makes you a "Navi_ite" :

1.Perseverance, Passion and Commitment

• Passionate about Navi's mission and vision

• Demonstrates dedication, perseverance and high ownership

• Goes above and beyond by taking on additional responsibilities

2.Obsession with high quality results

• Consistently creates value for the customers and stakeholders through high quality outcomes

• Ensuring excellence in all aspects of work

• Efficiently manages time, prioritizes tasks, and achieves higher standards

3.Resilience and Adaptability

• Adapts quickly to new roles, responsibilities, and changing circumstances, showing resilience and agility

:

• At Navi, the ML team is the backbone behind scalable and efficient platform capabilities to manage the entire model-lifecycle: feature-store pipelines, auto-train and retrain capabilities, templatized model-deployments, out-of-the-box real-time monitoring and observability platform for tracking NFR metrics, data & model drifts.
• We're not just keeping up with innovation: we're setting the pace. Our team is constantly pushing the boundaries and also developing in-house data-products & solutions extracting value from alternate sources of data powering use-cases across fintech sectors : Lending, Insurance, Investments, UPI that amplify business growth, enhance customer experiences, and streamline operational processes.
• Our work isn't confined to a single domain. We tackle a diverse set of problem statements, from GenerativeAI to NLP to computer vision to speech recognition. Each day brings a new challenge and a new opportunity for breakthroughs.
• When you join us, you're not just taking a job; you're becoming a part of a movement. A movement that's making a tangible difference in the fintech landscape, one innovative solution at a time.

Ready for a transformative career journey? Join us at Navi and be a part of a team that's shaping the future of fintech.

What you gain by working with the ML team at Navi:

• Own your journey from start to finish: Take pride in having end-to-end ownership of your projects. You won't just be a cog in the machine; you'll be the architect, designer, and implementer of cutting-edge product/platform solutions that drive our business forward.
• Build state-of-the-art capabilities: You get a chance to build and contribute to feature-extraction solutions(tapping into plethora of sources of data), in-house feature-store, auto-ml pipelines, ds-model-serving platform, real-time-monitoring-system to tackle data/model/business-metric drifts. Our high-growth, agile environment offers a treasure trove of data, giving you the freedom to experiment, innovate, and make data-driven decisions that matter.
• Make tangible impact: Your work won't just sit on a shelf; it will make waves. By closely collaborating with stakeholders across departments, you'll have the opportunity to design and develop solutions that not only solve complex problems but also make a meaningful impact on the industry and lives of millions of Indians.
• Personal growth: Collaborate with a diverse group of high-performing professionals who are as passionate about the field as you are. Our culture fosters continuous learning and upskilling, setting you up for ongoing success and accelerated career growth.

What we are looking for:

• Bachelor's or Master's in Engineering or equivalent.
• Minimum 2+ years of experience in applied machine learning.
• Strong proficiency in at least one of the following languages: Scala, Kotlin, Python, Go.
• Should have worked on large-scale data-processing technologies like spark
• Drive to explore, improve, enhance, automate, and optimize distributed systems and tools to meet evolving business needs.
• Demonstrable coding practices, including meticulous design documentation, thorough unit testing, peer code reviews, and a preference for agile methods.
• Experience of working with data scientists, engineering and product teams to develop platform capabilities and deploy ML models at scale
• Strong interpersonal skills, showcasing effective stakeholder management.
• Excellent verbal and written communication skills.

Senior Software Engineer (Search/Information Retrieval/ML)

We're seeking an experienced Search/Information Retrieval Engineer to design, develop, and optimize search solutions that deliver exceptional user experiences. The ideal candidate will combine strong software engineering skills with deep knowledge of information retrieval systems.

Responsibilities

• Design and implement advanced search functionality using modern search technologies (such as Elasticsearch, Solr, or similar platforms)
• Develop high-quality, scalable search applications with focus on relevancy, performance, and user experience
• Create and optimize search algorithms, ranking models, and retrieval methods
• Create Knowledge Graphs from various corporate data sources
• Implement and fine-tune query understanding, text analysis, and relevance scoring
• Analyze and maintain existing search infrastructure and applications
• Design and execute A/B tests to measure search quality improvements
• Develop efficient indexing strategies and data preparation pipelines
• Implement machine learning models for search ranking
• Discover and fix programming bugs
• Monitor and optimize search performance metrics
• Create and maintain documentation for search systems

Required Qualifications

• Bachelor's degree or equivalent experience in Computer Science, Information Science, or related field
• 5+ years of experience
• 3+ years of experience developing search solutions
• Strong proficiency in at least one programming language (Java, Python, or similar)
• Hands-on experience with search engines (Elasticsearch, Solr, or similar)
• Strong understanding of information retrieval concepts (TF-IDF, BM25, vector search)
• Expertise in SQL databases and experience with NoSQL solutions
• Experience with text processing, NLP, and relevance tuning
• Strong analytical and problem-solving skills

Preferred Qualifications

• Degree in Computer Science or related field
• Knowledge of modern neural search techniques and vector embeddings
• Experience with Knowledge Graphs/ Graph RAG and related infrastructure (Neo4J etc)
• Familiarity with relevance evaluation metrics (NDCG, MRR, MAP)
• Experience with large-scale distributed systems

Technical Skills

• Search Engines: Elasticsearch, Solr, or similar
• Programming Languages: Java, Python, Scala
• Databases: SQL, MongoDB, or similar

Soft Skills

• Strong communication abilities to explain technical concepts
• Collaborative mindset for cross-functional team work
• Detail-oriented with strong focus on quality
• Self-motivated and able to work independently
• Passion for solving complex search problems

What We Offer

• Opportunity to work on challenging search problems at scale
• Collaborative and innovative work environment
• Professional development opportunities
• Competitive salary and benefits package
• Flexible work arrangements

The successful candidate will join a dynamic team focused on delivering best-in-class search experiences, with opportunities to work on challenging problems and implement cutting-edge search technologies.

Job Title: MLOps Engineer

Urgent - High Priority requirement.

1. Location - Hyderabad

2. Interview Rounds - 4 round.

3. Contract - 12 Months

About Client:

We are a fast-growing boutique data engineering firm that empowers enterprises to manage and harness their data landscape efficiently. Leveraging advanced machine learning (ML) methodologies,

Job Overview:

We are seeking a highly skilled and motivated MLOps Engineer with 3-5 years of experience to join our engineering team. The ideal candidate should possess a strong foundation in DevOps or software engineering principles with practical exposure to machine learning operational workflows. You will be instrumental in operationalizing ML systems, optimizing the deployment lifecycle, and strengthening the integration between data science and engineering teams.

Required Skills:

Hands-on experience with MLOps platforms such as MLflow and Kubeflow.

Proficiency in Infrastructure as Code (IaC) tools like Terraform or Ansible.

Strong familiarity with monitoring and alerting frameworks (Prometheus, Grafana, Datadog, AWS CloudWatch).

Solid understanding of microservices architecture, service discovery, and load balancing.

Excellent programming skills in Python, with experience in writing modular, testable, and maintainable code.

Proficient in Docker and container-based application deployments.

Experience with CI/CD tools such as Jenkins or GitLab CI.

Basic working knowledge of Kubernetes for container orchestration.

Practical experience with cloud-based ML platforms such as AWS SageMaker, Databricks, or Google Vertex AI.

Competency in Linux shell scripting and command-line operations.

Proficiency with Git and version control best practices.

Foundational knowledge of machine learning principles and typical ML workflow patterns.

Good-to-Have Skills:

Awareness of security practices specific to ML pipelines, including secure model endpoints and data protection.

Experience with scripting languages like Bash or PowerShell for automation tasks.

Exposure to database scripting and data integration pipelines.

Experience & Qualifications:

3-5+ years of experience in MLOps, Site Reliability Engineering (SRE), or Software Engineering roles.

At least 2+ years of hands-on experience working on ML/AI systems in production settings.

Deep understanding of cloud-native architectures, containerization, and the end-to-end ML lifecycle.

Bachelor's degree in Computer Science, Software Engineering, or a related technical field.

Relevant certifications such as AWS Certified DevOps Engineer - Professional are a strong plus.

Appnext offers end-to-end discovery solutions covering all the touchpoints users have with their devices. Thanks to Appnext's direct partnerships with top OEM brands and carriers, user engagement is achieved from the moment they personalize their device for the first time and throughout their daily mobile journey.

Appnext 'Timeline', a patented behavioral analytics technology, is uniquely capable of predicting the apps users are likely to need next. This innovative solution means app developers and marketers can seamlessly engage with users directly on their smartphones through personalized, contextual recommendations.

Established in 2012 and now with 12 offices globally, Appnext is the fastest-growing and largest independent mobile discovery platform in emerging markets.

As a Machine Learning Engineer, you will be in charge of building end-to-end machine learning pipelines that operate at a huge scale, from data investigation, ingestions and model training to deployment, monitoring, and continuous optimization. You will ensure that each pipeline delivers measurable impact through experimentation, high-throughput inference, and seamless integration with business-critical systems. This job combines 70% machine learning engineering and 30% algorithm engineering and data science.

We're seeking an Adtech pro who thrives in a team environment, possesses exceptional communication and analytical skills, and can navigate high-pressure demands of delivering results, taking ownership, and leveraging sales opportunities.

Responsibilities:

• Build ML pipelines that train on real big data and perform on a massive scale.
• Handle a massive responsibility, Advertise on lucrative placement (Samsung appstore, Xiaomi phones, TrueCaller). Train models that will make billions of daily predictions and affect hundreds of millions users.
• Optimize and discover the best solution algorithm to data problems, from implementing exotic losses to efficient grid search.
• Validate and test everything. Every step should be measured and chosen via AB testing.
• Use of observability tools. Own your experiments and your pipelines.
• Be Frugal. Optimize the business solution at minimal cost.
• Advocate for AI. Be the voice of data science and machine learning, answering business needs.
• Build future products involving agentic AI and data science.
• Affect millions of users every instant and handle massive scale

Requirements:

• MSc in CS/EE/STEM with at least 5 years of proven experience (or BSc with equivalent experience) as a Machine Learning Engineer: strong focus on MLOps, data analytics, software engineering, and applied data science- Must
• Hyper communicator: Ability to work with minimal supervision and maximal transparency. Must understand requirements rigorously, while frequently giving an efficient honest picture of his/hers work progress and results. Flawless verbal English- Must
• Strong problem-solving skills, drive projects from concept to production, working incrementally and smart. Ability to own features end-to-end, theory, implementation, and measurement. Articulate data-driven communication is also a must.
• Deep understanding of machine learning, including the internals of all important ML models and ML methodologies.
• Strong real experience in Python, and at least one other programming language (C#, C++, Java, Go ). Ability to write efficient, clear, and resilient production-grade code. Flawless in SQL.
• Strong background in probability and statistics. Experience with tools and ML models Experience with conducting A/B test.
• Experience with using cloud providers and services (AWS) and python frameworks: TensorFlow/PyTorch, Numpy, Pandas, SKLearn (Airflow, MLflow, Transformers, ONNX, Kafka are a plus).
• AI/LLMs assistance: Candidates have to hold all skills independently without using AI assist. With that candidates are expected to use AI effectively, safely and transparently.

Preferred:

• Deep Knowledge in ML aspects including ML Theory, Optimization, Deep learning tinkering, RL, Uncertainty quantification, NLP, classical machine learning, performance measurement.
• Prompt engineering and Agentic workflows experience
• Web development skills
• Publication in leading machine learning conferences and/or medium blogs.

Job Title: Machine Learning Engineer

Experience: 5-7 years

Location: Bangalore

Key Responsibilities:

- Design, develop, and deploy machine learning models and algorithms using Python

- Collaborate with cross-functional teams to define project requirements and deliverables

- Analyze large datasets to extract insights and inform decision-making

- Implement and optimize machine learning algorithms using frameworks like TensorFlow, PyTorch, and scikit-learn

- Evaluate model performance, conduct A/B testing, and iteratively improve model accuracy and efficiency

Required Skills:

- Technical Skills:

- Proficiency in Python programming

- Experience with machine learning frameworks (TensorFlow, PyTorch, Keras)

- Strong understanding of data analysis techniques and statistical methods

- Familiarity with data engineering tools (SQL, Hadoop, Spark)

- Soft Skills:

- Excellent problem-solving skills and attention to detail

- Strong communication skills to convey complex technical concepts effectively

Preferred Skills:

- Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices

- Familiarity with Agile methodologies and DevOps practices

- Knowledge of specific domains like natural language processing (NLP) or computer vision

Education:

- Bachelor's or Master's degree in Computer Science, Mathematics, or a related field

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.

We are looking for an experienced Machine Learning Engineer to join our team. The ideal

candidate should have a strong background in developing, implementing, and deploying

machine learning models on edge platforms. With at least 5 years of overall experience and at

least 3 years of machine learning experience, you will significantly contribute to our projects,

driving innovation and delivering high-quality solutions.

Responsibilities:

Design, develop, and deploy machine learning models and algorithms on the edge

platforms.

Perform data analysis and feature engineering to enhance model performance.

Collaborate with cross-functional teams to integrate ML solutions into existing systems.

Monitor and maintain deployed models, ensuring optimal performance and reliability.

Stay current with the latest advancements in machine learning and AI.

Document processes and best practices for machine learning workflows.

Troubleshoot and resolve issues related to ML models and data pipelines.

Experience & Background Requirement:

Bachelor's or Master's degree in Engineering or equivalent.

Minimum of 7+ years of overall experience.

Minimum of 7 years of machine learning experience.

Proficiency in programming languages such as Python, C, C++.

Experience with any of HW platforms like NXP, NVidia, Qualcomm, Synaptcis.

Strong understanding of machine learning algorithms and techniques (e.g., regression,

classification, clustering, neural networks).

Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch,

Scikit-learn, Pandas, Numpy, Matplotlib, OpenCV).

Knowledge of data preprocessing, feature engineering, and model training/evaluation.

Experience with data storage and processing technologies (e.g., SQL, JSON, XML).

Excellent problem-solving and analytical skills.

Strong communication and collaboration abilities.

Experience of streaming and GUI development is an advantage.

iMerit is a leading AI data solutions company providing high-quality data across computer vision, natural language processing and content services that power machine learning and artificial intelligence applications for large enterprises. iMerit's customers are able to focus on the algorithms that drive the AI systems embedded in their products and operations, while the iMerit team of trained specialists handles all data enrichment work required to support and refine such systems.

Position - ML Engineering Manager

Domain - AI

Experience - 12+ Years

Location - Bangalore

IMerit works with multiple clients who are spread across the spectrum in developing ML and AI solutions. iMerit uses ML/AI to automate and improve the quality of the productized services that we offer to our customers in the data annotation space. The iMerit ML team is at the forefront of developing various automation solutions across different industry verticals, technology domains and data modalities. We are looking for an experienced, hands-on engineering manager who will lead the ML team in their various efforts.

Responsibilities:

Team Leadership

• Lead and mentor a team of machine learning and computer vision engineers.
• Foster a collaborative environment that encourages innovation and continuous improvement.

Technical Leadership

• Oversee the design, development, and deployment of machine learning models.
• Ensure adherence to best software/ML development practices, coding standards,

and quality assurance processes.

• Oversee the productionization of scalable ML solutions.
• Evaluate and select appropriate tools, frameworks, and technologies.
• Participate in architecture, design and code reviews.

Project Management

• Monitor project progress, identify risks, and implement mitigation strategies.
• Ensure timely delivery of projects, meeting quality standards and budget constraints.

Strategic Planning

• Align machine learning initiatives with the company's strategic goals.
• Identify opportunities for leveraging ML to create business value.
• Contribute to technology roadmaps and long-term planning.

Collaboration

• Work closely with other engineering teams, data analysts, and business stakeholders to define problem statements and to operationalize solutions.
• Facilitate communication and collaboration across teams and departments.
• Represent the team in cross-functional meetings and executive briefings.

Required Skills:

• 12+ years of work experience with a solid background in software engineering and machine learning.
• Minimum 7 years of experience in machine learning with at least 5 years in a leadership or managerial role. At least 3 years of experience in building production-grade scalable ML pipelines.
• Advanced proficiency in Python and ML frameworks like Tensorflow, Keras, Scikit-learnor PyTorch. Proficiency in a system language such as Rust, C++, or Java would be an advantage.
• Proven ability to deliver a shippable solution given conflicting and ambiguous requirements.
• Experience with cloud build, deployment, and orchestration tools.
• Experience with MLOps tools and frameworks.
• Experience with DevOps, Big Data and Cloud platforms is a big plus.
• Demonstrable analytical and debugging skills.
• Excellent communication and interpersonal skills.
• In-depth awareness of the latest technologies and trends in Generative AI would be an advantage
• Self-motivated, with an ability and in learning new technologies and adapting quickly to new requirements and environments.

Immediate Joiners Only - Please apply only if you're available to start right away. If you're currently serving a notice period or cannot join immediately, we kindly ask that you refrain from applying.

We're only interested in candidates who have experience working with AI Agent frameworks-such as LangChain, Langraph , AutoGen, CrewAI, Auto-GPT, or custom-built systems. If you've explored multi-agent coordination, autonomous task execution, memory management, or tool-based reasoning using LLMs,

Position: Machine Learning Engineer (Entry-Level, LLM Focus)

Location: Fully Remote (India-Based)

Start Date: Immediate

Format: Full time

Compensation: Competitive Salary + Strong Equity Offering + Benefits

Who We Are

Gabeo.ai is a cutting-edge health tech startup based in the Bay Area (USA), collaborating with industry leaders like Astrana Health, Athena Health and Rebound Orthopedics. Our goal? Transform the healthcare revenue cycle by using advanced AI to tackle denied medical claims-one of the sector's biggest financial headaches.

At Gabeo.ai, we pride ourselves on:

• Innovation: We push boundaries and welcome out-of-the-box thinking.
• Collaboration: We're a tight-knit team that values open communication.
• Impact: Your work will directly influence our AI-driven products and customer outcomes.

Role Overview

At Gabeo.ai, we are pioneering AI Agent Frameworks designed to automate and optimize complex tasks within healthcare revenue cycle management. These intelligent agents leverage Large Language Models (LLMs) and specialized domain knowledge to autonomously analyze claim data, predict denials, and execute strategic interventions. By continuously learning from real-world feedback and historical patterns, our agent-based systems evolve over time, adapting to new payer policies and medical coding updates. The result is a robust, scalable framework that reduces manual workload, accelerates claim resolution, and drives financial efficiency for healthcare providers. We're seeking an entry-level Machine Learning Engineer with a keen interest in Large Language Models (LLMs)and NLP. You'll join our global team to develop and refine AI models for U.S. healthcare revenue cycle management. This position offers real-world exposure to cutting-edge AI in a domain that truly needs innovation.

Note: While we encourage applications from candidates who have graduated from top-tier Indian institutes (e.g., IIT, NIT, IIIT, BITS, etc.), we welcome all qualified applicants who demonstrate strong fundamentals and a passion for AI.

Key Responsibilities

• Model Development: Collaborate on designing, developing, and optimizing ML models-AI Agents - particularly LLMs-for tasks like claim denial analysis and predictive analytics.
• Data Handling: Assist in data collection, preprocessing, and feature engineering specific to healthcare RCM (Revenue Cycle Management) problems.
• Research & Experimentation: Stay updated with the latest AI/ML trends and apply new techniques to improve model performance.
• Integration & Deployment: Work closely with senior engineers to integrate models into production environments, ensuring scalability and reliability.
• Performance Monitoring: Help monitor model accuracy and efficiency, proposing iterative improvements based on feedback and metrics.

Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related fields.
• Graduates from IIT, NIT, IIIT, BITS, or equivalent institutions are strongly encouraged to apply.
• Technical Skills:
• Proficiency in Python and popular ML frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with NLP techniques, LLMs, and transformer-based architectures.
• Problem-Solving: Eagerness to tackle complex datasets and real-world issues in the U.S. healthcare domain.
• Team Player: Ability to communicate effectively with a distributed team, including data scientists, product managers, and domain experts.

What We Offer

• Real-World Impact: Contribute to AI solutions that directly benefit healthcare providers and patients.
• Mentorship & Growth: Learn from experienced data scientists and healthcare tech specialists.
• Competitive Package: Enjoy a market-aligned salary plus strong equity for an ownership stake in Gabeo.ai's success.
• Remote Flexibility: Work from anywhere in India, collaborating with a global, diverse team.

Why Join Gabeo.ai?

• High-Growth Environment: We're rapidly expanding, offering plenty of opportunities for leadership and skill development.
• Cutting-Edge AI: Work on advanced ML/AI projects that push the boundaries of LLM applications in healthcare.
• Startup Culture: Enjoy a fast-paced setting where your ideas can quickly translate to tangible impact.

How to Apply

Ready to kick-start your AI career and transform healthcare with Gabeo.ai? Apply now with your CV, Github/portfolio links, and a brief description of your most exciting AI/ML project.

Please Note: We are currently accepting applications only from India-based candidates who are either recent graduates or early-career professionals. While a background in US healthcare is a plus, it is not mandatory-we value strong ML fundamentals and a willingness to learn.

Join us in redefining healthcare revenue cycle management through the power of AI and LLMs!

Talent Worx is a growing services & recruitment consulting firm, we are hiring for our client which is a leading provider of financial intelligence, data analytics, and AI-driven solutions, empowering businesses worldwide with insights for confident decision-making. Join to work on cutting-edge technologies, drive digital transformation, and shape the future of global markets.

Job Title: Machine Learning Engineer

Location: Gurgaon / Hyderabad

Experience: 5-14 years

Key Responsibilities:

• Design, build, and deploy scalable ML models for information extraction and NLP.
• Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Work with large-scale data processing frameworks (Apache Spark) to optimize ML solutions.
• Develop and maintain cloud-based data pipelines (AWS/GCP) for streaming and batch processing.
• Implement MLOps best practices including CI/CD pipelines, automated testing, and model monitoring.
• Deploy containerized ML applications using Docker and Kubernetes.
• Collaborate with data engineers, software developers, and product teams to integrate ML solutions.
• Stay updated on emerging ML, NLP, and AI trends to enhance models.

Qualifications & Skills:

• 5+ years of experience in Machine Learning, NLP, and MLOps.
• Strong expertise in Python and ML/NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face).
• Experience with Apache Spark for large-scale data processing.
• Hands-on experience in cloud-based ML development (AWS/GCP).
• Strong understanding of data preprocessing, feature engineering, and model training.
• Proficiency in SQL (big data experience is a plus).
• Version control experience with Git, GitHub, or Azure DevOps.
• Excellent problem-solving, debugging, and optimization skills.

Nice to Have:

• Experience with LangChain for LLM-based applications.
• Knowledge of Core Java 17+ (preferably Java 21+), Apache Kafka, and Apache Avro.
• Exposure to JVM-based languages such as Kotlin or Scala.

Job Description:

At TuriyamAI, we are pioneering world leading GenAI semiconductor solutions from India, for India and the World. Our breakthrough solutions are set to redefine the future of AI computing, driving unparalleled efficiency, performance, and accessibility for enterprises worldwide.

Responsibilities:

• Implement quantization techniques to optimize model performance and efficiency.
• Experience with inference optimizations at node and cluster scale
• Experience developing, modifying, optimizing inference frameworks such as vLLM, SGLang.
• Optimize multi-modal LLM deployments, prompt caching, RAG workflows, etc.
• Collaborate with HW and SW teams to drive innovations and optimizations into the product deployments
• Stay up-to-date with the latest advancements in machine learning and AI technologies, and apply them to improve our products and services.

Requirements:

• Bachelor's or Master's or Ph.D. degree in Computer Science, Engineering, or a related field.
• Must have strong background in quantization and model optimization techniques.
• Experience in deploying machine learning models at scale in production environments.
• Proficiency in PyTorch.
• Solid understanding of machine learning algorithms and their implementation on accelerators.
• Excellent problem-solving skills and the ability to work independently as well as part of a fast paced team in a startup environment.
• Strong communication skills to effectively convey technical concepts to non-technical stakeholders.

Preferred Qualifications / Experience:

• Experience with fine-tuning and distillation of large language models (LLMs)
• Experience with cloud platforms such as AWS, Google Cloud, or Azure.

Familiarity with MLOps practices and tools for model deployment and monitoring.

Benefits:

Competitive salary and benefits package.

Opportunity to work on cutting-edge AI technology.

Collaborative, dynamic and inclusive work environment.

Professional growth and development opportunities.

How to Apply: Interested candidates are invited to submit their resume and a cover letter detailing their relevant experience and why they are a good fit for this role to

Title: STC / LTC - Mid-Level AI Engineer (Azure AI/ML Specialist)

Relevant Experience: 4-6 Years

Location: Remote (Preferred Location: Chennai)

Type of Hire: Open to both Persons with Disabilities (PwD) and Non-PwD candidates

Availability: Immediate Joiners Preferred

About Us

Ampera Technologies is a leading IT services company providing innovative technology solutions and digital services to clients globally.

Position Overview

We are seeking a Mid-Level AI Engineer to join our AI Delivery team, with strong proficiency in Microsoft Azure AI/ML tools to develop, fine-tune, and deploy Large Language Models (LLMs) and enterprise-ready AI solutions.

You will work hands-on with Azure's advanced AI ecosystem-including Azure Machine Learning, Azure AI Foundry, Azure OpenAI, and related services-to deliver scalable, production-grade models and AI-powered workflows.

This is an exciting opportunity to contribute to next-generation AI solutions, while working in an inclusive and innovation-driven environment.

Key Responsibilities

Prompt Engineering & LLM Optimization

• Design and iterate on high-performing prompts using Azure Machine Learning Workbench, applying robust performance tracking and versioning.
• Build Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search and vector databases to enhance model relevance with domain-specific knowledge.

Model Fine-Tuning & Deployment

• Fine-tune LLMs such as GPT-4, Phi-3, and other models using Azure AI Foundry, with techniques including model distillation, hyperparameter tuning, and multimodal data integration.
• Deploy models to production using Azure Kubernetes Service (AKS) or Azure Container Apps, ensuring scalability, reliability, and cost-effectiveness through managed endpoints.

AI Toolchain Integration & Workflow Automation

• Develop agentic AI workflows with Azure AI Agent Service to automate tasks such as document generation, code modernization, meeting preparation, and other enterprise use cases.
• Leverage Azure AI Evaluations and Prompt Flow for systematic testing, benchmarking, and mitigation of bias and compliance risks, aligned with Responsible AI principles.

Collaboration, Monitoring & Governance

• Collaborate with DevOps and Cloud Operations teams to configure Azure Monitor for real-time AI model performance monitoring and operational cost optimization.
• Utilize Azure AI Content Safety to review AI-generated outputs for ethical and compliance standards.

Required Qualifications

Technical Expertise

• Strong proficiency in Azure Machine Learning for full ML lifecycle management, including experiment tracking, model registry, and MLOps.
• Experience with Azure AI Foundry Models for model evaluation, customization, and seamless deployment via unified APIs.
• Familiarity with Azure AI Services (Document Intelligence, Vision, Translator) for multimodal AI applications.

Tools & Frameworks

• Practical experience with Azure OpenAI Service for fine-tuning and deploying GPT-based models.
• Expertise in building Azure AI Search pipelines for vector database management and RAG-based retrieval.

Certifications

• Microsoft Azure AI Engineer Associate certification (or equivalent) is highly desirable.

Preferred Skills

• Experience with Semantic Kernel or AutoGen for building multi-agent AI workflows.
• Knowledge of Azure AI Foundry Local for hybrid cloud or edge AI deployments.
• Familiarity with LLMOps best practices for monitoring and improving deployed models continuously.
• Understanding of AI Governance and Responsible AI frameworks and tools.

Greetings from TCS!

Job Title: ML Senior Developer

Skillset : NLP, LLM, AIML, Prompt engineering, and Finetuning

Location: Bangalore

Experience Range: 5 - 12 years

Must-have skills

• 5+ years experience in NLP,ML,AI area.
• Hands on experience in designing systems with ML backbone.
• Experience in NLP queries, LLM prompts and finetuning.
• NLP, LLM, AIML,Prompt engineering, LLM finetuning

What you will enjoy doing

• You will develop, train, test and deploy machine learning models in various fields such as

computer vision, LLMs, tabular and time series data.

• Experimenting with novel deep learning based technologies such as self-supervised learning

and generative AI will also be part of your tasks

• You will support in setting up the MLOps infrastructure for existing and new AI products

• Additionally you will work directly with customer data and set up data pipelines to collect,

curate, transform and version data

You'll be working in the Artificial Intelligence team, AI global corporate division engaged with real business challenges and opportunities in multiple countries. Focus of this role is to support the AI team with extending existing and building new AI products for a vast amount of uses cases across

business and value chain. You'll collaborate across different business and corporate functions in international team composed of Project Managers, Data Scientists, Data and Software Engineers

in the AI team and others in the Global AI team.

As a Machine Learning Enginee, you will be working closely with our global AI team to create and

implement sustainable AI models, algorithms, and software solutions for our global industrial gases and engineering services operations. You will participate in the collection, analysis, interpretation, and output of large amounts of data using advanced AI techniques like deep learning, NLP, and computer vision.

What Makes You Great

• You have a Bachelor or Masters Degree in Data Science, Computational

Statistics/Mathematics, Computer Science or related field

• You know the basics of neural networks and have an initial practical experience with deep

learning frameworks like PyTorch and Tensorflow.

• You have experience in backend and API development with Python (FastAPI, Flask) or similar

• You demonstrate knowledge of and basic practical experience with Object Oriented

Programming, design patterns, algorithms and data structures, version control systems (e.g.

Git)

• Having basic experience with cloud platforms (e.g. Azure), Docker and Kubernetes is a plus

• Fluent English

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.

Senior Machine Learning Engineer

Experience: 7 to 11 years

Preferred Locations: Chennai, Bangalore, Hyderabad

We are looking for a Senior ML Engineer who will work on a broad range of cutting-edge data analytics and machine learning problems across a variety of industries.

Key Responsibilities:

• Engage with clients to understand their business context
• Lead a team of data scientists and engineers to embed AI and analytics into the business decision processes.
• Perform a role that involves a combination of hands-on contribution and customer engagement.
• Switch between roles of an Individual Contributor, team member and solution architect as demanded by each project.
• Design, develop, and deploy ML models in a production environment.
• Leverage Python, PySpark, and machine learning tools to build scalable, maintainable solutions.
• Work on any cloud platforms, with strong hands-on experience in SageMaker or Databricks.
• Implement MLOps frameworks such as MLflow or Kubeflow for seamless model lifecycle management.
• Collaborate with cross-functional teams and apply best software engineering practices to ML projects.
• Monitor model performance and ensure model stability through deployment and versioning pipelines.
• Contribute to CI/CD pipelines for ML workflows (bonus if you've built or maintained one before).

Required Skills and Expertise:

• 6+ years exp of which 3+ years of relevant data science experience and at least 3 years of software development experience.
• Experience in devising creative analytical approaches to solve business problems
• Developing and enhancing algorithms and models to solve business problem
• Maintaining all models along with development and updating of code and process documentation
• Designing a solution approach, leading a team to deploy and maintain it in production.
• Proficient in Structured programming language is a must - such as Python, C/C++, Java is mandatory.
• Cloud concepts and significant hands-on experience with at least one cloud provider. Should be knowledgeable about the pros and cons of the various services and comfortable discussing the tradeoffs with stakeholders.
• Strong SQL skills.
• Good knowledge of Data science approaches, machine learning algorithms and statistical methods.
• ETL and Data Engineering pipelines using Spark/PySpark.
• Workflow orchestration tools like Airflow.
• Excellent written and verbal communication skills.

Job Title: Senior Software Development Engineer - MLOps

Location: Bangalore, India

Experience Level: 3-5 years

Budget: 21 LPA

Role Overview

Were looking for a Python Engineer who thrives in dynamic environments and has a strong grasp of software architecture and distributed systems. Youll design and build core backend components that power our AI-driven warehouse intelligence platform. This is a high-impact role with opportunities to solve complex systems problems, work closely with cross-functional teams, and drive engineering best practices.

What You'll Do

• Design, implement, and maintain Python-based tools and services across MLOps, data pipelines, and configuration management.
• Architect scalable and modular components for high-throughput data processing using technologies like Kafka.
• Collaborate with ML engineers, platform developers, and DevOps to build efficient and maintainable infrastructure.
• Contribute to engineering discussions on design patterns, performance, and scalability. Write clean, modular, and well-documented code following solid software engineering principles. T
• Take ownership of features end-to-end-from ideation and design to deployment and monitoring.

What We're Looking For

• 35 years of experience developing and maintaining Python applications in production environments.
• Strong software design skills with a focus on modularity, scalability, and fault-tolerance. Experience with Kafka or similar distributed messaging systems.
• Solid understanding of version control (Git), CI/CD workflows, and containerization tools like Docker.
• Exposure to any of the following areas: MLOps frameworks (e.g., MLflow, DVC, Airflow) FastAPI or similar Python-based web frameworks Infrastructure-as-code and structured config formats (e.g., YAML, JSON, Ansible)

Nielsen is seeking an organized, detail oriented, team player, to join the Engineering team in the role of Machine learning 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.

Qualifications:

• Experience having led multiple projects leveraging LLMs, GenAI and Prompt Engineering
• Exposure to real-world MLOps deploying models into production adding features to products
• Knowledge of working in a cloud environment
• Strong understanding of LLMs, GenAI, Prompt Engineering and Copilot

Responsibilities:

• Bachelor's degree in Computer Science or equivalent degree
• 6+ years of software experience Experience with Machine learning frameworks and models
• The ML Engineer is expected to fully own the services that are built with the ML Scientists. This cuts across scalability, availability, having the metrics in place, alarms/alerts in place - and be responsible for the latency of the services
• Data quality checks & onboarding the data on to the cloud for modeling purposes
• Prompt Engineering, FT work, Evaluation, Data
• End-end AI Solution architecture, latency tradeoffs, LLM Inference Optimization, Control Plane, Data Plate, Platform Engineering
• Comfort in Python and Java is highly desirable
• The ML Engineer will head the ML engineering for a pod and be the technical leader for all ML/AI Engineering issues in a delivery pod

Glance - An InMobi Group Company

Founded in 2019, Glance is a consumer technology company that operates some of the most disruptive digital platforms including Glance, Roposo, and Glance TV. Glance has redefined the way the internet is consumed on the lock screen, removing the need to search for and download apps. Over 400 million smartphones now come enabled with Glance's next-generation internet experience.

Roposo has revolutionized commerce by launching a destination for creator-led live entertainment commerce. Glance TV is changing the way consumers engage and interact with their televisions.

Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information, visit and

What should you know about joining Glance?

At Glance, we walk the talk - free yourself, dream big, and chase your passion! On joining, you'll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.

While you work, we'll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids - even the furry ones - to the office!

What you will be doing?

Glance is looking for a Data Scientist who will design and develop recommendation systems on high volume, diverse "big data" sources using advanced mathematical, statistical, querying, and reporting methods. Will use machine learning techniques and statistical analysis to predict outcomes and behaviors.

• Develop and deploy machine learning models with a focus on quick, reliable experimentation to validate features and hypotheses. Our team values speed and quality in experimentation.
• Assist in building and maintaining machine learning pipelines, aiding in tasks such as data preparation, model training, and evaluation.
• Collaborate closely with Designers, UX Researchers, Product Managers, and Software Engineers to contribute to the integration of machine learning solutions into Glance's products.
• Monitor the health and performance of machine learning models, using statistical methods to ensure their effectiveness.
• Conduct preliminary research and development in machine learning techniques to enhance Glance's product capabilities.
• Additionally, stakeholder management is needed. It will involve being the interface with internal stakeholders such as our Product, Engineering, Data, Infrastructure, and Business teams.
• You will work in a multi-functional team environment. You will collaborate and benefit from the skills of a diverse group of individuals from teams such as engineering, product, business, campaign management and creative development.
• We are a company that innovates and demonstrates our thought leadership to the world. We encourage and support all team members to write blogs, commentary and case studies published on the Glance blog. We also support team members across our ML/AI team to speak at industry conferences and represent Glance's work.

The experience we need

• Candidates are expected to have deep expertise and experience in AI/ML, Recommendation Systems and Data Science, particularly at scale. Familiarity with big data processing and cloud computing will be critical to succeed in this environment.
• In addition to possessing a mathematical aptitude, they need to be competent with data science languages and tools which will enable them to design scalable solutions for our advertising products, implement proof-of-concept, and evaluate them offline and online. They will also need to work with other engineers to take these solutions to live production and drive real business value.
• Most importantly, we look for a passion to investigate and learn about the world from data, to ask interesting and provocative questions, and be driven to put real models into production that drive real business value.
• We are open to diverse academic backgrounds, providing an intent to think and problem-solve like a data scientist. Our team includes engineers, mathematicians, computer scientists, physicists, economists and social scientists - a rock-star data scientist can come from any academic field.

Qualifications

• Bachelors/Master's in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. Or Bachelor's with additional experience. PhD a plus.
• 10+ years of ML industry experience working in Data Science teams, ideally in recommendation systems and personalization at scale. You would have applied algorithms and techniques such as NLP, Reinforcement Learning, Time Series, etc. from Machine Learning, Deep Learning, and Statistics or other domains in solving real world problems and understand the practical issues of using these algorithms especially on large datasets.
• Comfortable with software programming and statistical platforms such as R, Python etc.
• Comfortable with the big data ecosystem and Apache Spark. Familiarity with Microsoft Azure, AWS, or Google Cloud/Vertex AI will be a bonus.
• Comfortable collaborating with cross-functional teams.
• Familiarity with challenges of the identity-less world, particularly for iOS and Android
• Excellent technical and business communication skills and should know how to present technical ideas in a simple manner to business counterparts.
• Possess a high degree of curiosity and ability to rapidly learn new subjects and technology

Dear Aspirants,

Greetings from ValueLabs!

We are looking for AIML Engineer

Role: AIML Engineer

Skill set: AI/ML, NLP, Deep learning, Python, LLM, Gen-AI, Rag Implementation.

Experience : 5+ Years

NP: Immediate

Location : Hyderabad - Hybrid

Job Description

- Proficiency in Python to manipulate data and draw insights from large data sets is a must. - Knowledge of a variety of machine learning techniques (clustering, decision trees, boosting, artificial neural networks, etc.) and their real-world advantages/drawbacks. - Knowledge of popular ML and non-ML libraries: TensorFlow, Torch, Sklenar, etc. - Solid understanding of machine learning concepts and techniques, particularly in NLP. - Experience on popular NLP and Computer vision libraries is a plus: Spacy, NLTK, OpenCV, - Knowledge of popular cloud infrastructure: Google Cloud, AWS, Microsoft Azure, - Experience in code management using Git Secondary Skills - Strong problem-solving skills and the ability to work collaboratively in a team environment. - Excellent written and verbal communication skills. - Experience in leveraging large language models (LLMs) and frameworks such as Lang Chain and Lang Smith for creating and optimizing AI-driven conversational applications.

Job Description:

Job Title: Senior AI/ML Engineer

Shift Timings: General Shift Timings

Location: INDIA, REMOTE, Work from Home

Experience required: 5 to 10 years

Job Description

We are looking for a Senior AI/ML Engineers to join our team and help us build intelligent, scalable, and impactful solutions. In this role, you'll contribute to all phases of the ML lifecycle, from ideation to deployment, and play a key role in delivering high-quality, production-ready applications.

• Skills and Responsibilities3-10 Years of work experience with Machine Learning and software development.
• Degree in computer science or related field.
• Proficient in Python & software development best practices.
• Excellent written and verbal communication skills in English.
• Ability to provide expert advice by communicating a structured narrative to non-technical staff and clients.
• A coaching & knowledge sharing mindset.
• Experience with deploying ML models to a large user base.
• Worked on one of the major Cloud providers (AWS, Azure, GCP).
• Familiarity with MLOps way of working.
• Took a leading technical role in a team structure (considered as a plus).
• an engineer that understands customer business needs and translate them into end-to-end technical solutions (from conception to deployment).
• Make applications that are carefully architected, scalable and robust through your combined skills in engineering and machine learning.
• Use Python to deploy production ready pipelines and ML models on the Cloud.
• Explore state-of-the art ML research and drive internal evaluation and adoption of cutting edge tools and frameworks.
• Are responsible for the high-quality delivery of your team's projects.
• Technically guide junior engineers.
• Deliver technical workshops for clients.
• Leverage your expertise to help sales qualify and land exciting projects.
• Take ownership to lead projects with confidence as a tech lead.