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Machine Learning Scientist (MLS-2) - New Initiatives

About Nykaa

Nykaa is India's leading beauty and lifestyle destination. We are a consumer-tech company offering a wide portfolio of beauty, personal care, and fashion products across online platforms and retail stores.

We are powered by technology and data, and our Data Science team plays a critical role in building intelligent, personalized, and seamless experiences for millions of customers. As we scale, we are investing heavily in foundational ML systems that enable real-time decisioning, automation, and GenAI-powered customer experiences.

Role Overview

As an MLS-2 (Machine Learning Scientist), you will work on high-impact ML projects across demand forecasting, supply chain optimization, marketing personalization, and fraud risk detection. You will contribute to model development, experimentation, and deployment of scalable ML solutions that directly influence inventory efficiency, marketing ROI, delivery predictability, and platform integrity. This is a hands-on role where you will work with senior scientists and engineers, translate business requirements into well-defined modeling tasks, and ensure high-quality model delivery.

Key Responsibilities

1. Machine Learning & Modeling

• Build and improve forecasting models using statistical and ML techniques such as ARIMA, Prophet, XGBoost, LSTMs, and transformer-based architectures under guidance from senior scientists.
• Develop models for coupon optimization, price elasticity, uplift modeling, and marketing attribution to improve personalization and campaign efficiency.
• Contribute to fraud detection models using anomaly detection, graph-based techniques, and unsupervised learning.

2. Supply Chain & Operational Modeling

• Support the development of algorithms for inventory planning, SKU allocation, and warehouse optimization using linear/integer programming and heuristic methods.
• Work on improving Estimated Delivery Date (EDD) accuracy using spatiotemporal, carrier, and operational signals.

3. Data Science & Analytics

• Translate loosely defined business problems into structured ML tasks.
• Conduct exploratory data analysis, feature engineering, model training, evaluation, and documentation.
• Build and maintain data pipelines in collaboration with Data Engineering teams.

4. Deployment & Productionization

• Work with engineering teams to productionize ML models using frameworks like MLflow, SageMaker, Databricks, and Spark.
• Monitor model performance, detect drifts, and contribute to continuous model improvements.

5. Collaboration & Communication

• Collaborate with Product, Engineering, Operations, and Marketing teams to deliver data-driven insights and solutions.
• Present analysis and model outcomes to cross-functional partners in a clear and structured manner.

Qualifications & Skills

Experience

• 2-5 years of hands-on experience in Machine Learning, Applied Statistics, or related fields.

Education

• Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative discipline.

Technical Skills

• Strong foundation in ML concepts including regression, tree-based methods, regularization, bias-variance tradeoffs, and probabilistic modeling.
• Experience with time-series modeling (ARIMA, ETS, Prophet); exposure to deep-learning-based forecasters (LSTM, TFT, DeepAR) is a plus.
• Working knowledge of optimization techniques (linear programming, heuristics, or RL concepts) is desirable.
• Good coding skills in Python and experience with ML libraries such as Scikit-learn, XGBoost, PyTorch/TensorFlow, Prophet, and PyMC/Stan (nice-to-have).
• Experience working with distributed data environments like Spark, Databricks, or AWS is a plus.

Business Skills

• Ability to break down business problems into analytical tasks.
• Strong analytical reasoning and problem-solving skills.
• Clear written and verbal communication skills.

What You'll Learn & Grow Into

• Building production-grade ML systems at scale.
• Designing optimization solutions for supply chain and logistics.
• Deep familiarity with causal inference and marketing science.
• Working with large-scale distributed data systems.
• Contributing to real-time decisioning systems and GenAI-powered experiences.

Qs to expect on:

• ML Foundational concepts like Bias-Variance Trade-Offs, Linear/Logistic regression, Tree Methods, Maximum likelihood Estimation, etc
• Statistical foundational concepts like Central Limit Theorem, A/B testing, statistical distributions, etc.
• The Error/Cost functions behind the ML methods that you recently worked on, and intuitions behind them.
• Time-Series Forecasting methods, including classical (ARIMA, ETS) and modern DL based methods(DeepAR, etc.)
• Formulate Business problems as optimization problems with techniques from Linear/Integer Programming, Genetic Algorithms, Reinforcement Learning, and heuristic optimization.
• Observational Causal Inference Methods like Inverse Propensity Weighting, Doubly Robust Methods. Foundational concepts like Causal Assumptions, Potential Outcome Framework, etc.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Job Description:

• Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
• Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems
• Strong grasp of statistics, probability, and the mathematics underpinning modern AI
• Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production
• Proven experience on at least one end-to-end GenAI or advanced NLP project: custom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions.
• Develop agentic AI workflows using LangChain, LangGraph, CrewAI, Autogen, or PhiData .
• Deploy and manage models using MLflow, Kubeflow, SageMaker, Docker, and Kubernetes .
• Monitor model performance, drift, and ensure scalability and robustness in production.
• Collaborate with cross-functional teams to align ML solutions with business and product goals.

Role Overview:

We are looking for a proactive and detail oriented professional to join our Information Technology Dept. The candidate will be responsible for Data Engineering, Analytics & Automation, Industrial IIOT and Machine Learning and contributing to the company’s global growth strategy.

Qualification & Experience:

Education: BE/B.Tech(IT/IS/CSE) MCA/M.Sc(Computer Science/Systems).

Length of Experience:

12 to 20 years in relevant field.

Desired Skills:

Data Engineering

Data Analytics tools like Power BI & Qlik Sense

Machine Learning & AI

Knowledge of Cloud Platforms

Key Responsibilities:

Data Analysis.

Process Automation.

Data Engineering.

Maintenance of projects in process automation.

Development and Support of different API’s (Python).

Development and support of ongoing project.

About Leegality:

We're India's very first Document Infrastructure Platform. Our mission? To completely transform how businesses handle paperwork, contracts, and getting digital consent.

We make critical paperwork flows faster, way more innovative, and completely compliant for Indian businesses. Over 2,000 companies, from huge players like HDFC and SBI Cards to super fast-growing ones like Razorpay and Cars24, trust us with their document workflows.

Beyond our core platform, we've launched "Deal Collaboration" (making contract negotiation a breeze) and "ConsentIn" (for easy, DPDP-compliant consent collection).

Basically, we're building the go-to execution layer for all modern paperwork. If that sounds exciting, come join us!

Curious about our impact? Check out our customer success stories here:

Our Culture:

At Leegality, we're all about trust, owning our work, transparency, and having a blast while building something meaningful.

These aren't just buzzwords; our team proved it by giving us an amazing 97 on the eNPS survey for FY 2023-24 (that's the highest among over 175 startups!).

We're always working to help our team grow and stay motivated. We offer cool perks like flexible hours, hybrid work, and bi-annual appraisals to make sure everyone has an awesome work environment.

If our culture vibes with you, ke