Data Scientist - LLM/RAG

Job Title : Data Scientist Machine Learning & Generative AI

About the Role :

We are seeking a highly skilled and forward-thinking Data Scientist with 4+ years of experience in building intelligent solutions using machine learning (ML) and generative AI. This role is pivotal in advancing our AI initiatives, particularly in deploying RAG (Retrieval-Augmented Generation) pipelines and building autonomous agents using cutting-edge frameworks like AutoGen and LangGraph.

You will join a collaborative, fast-paced, and innovative environment where your contributions will directly shape the way we deliver AI-driven insights and products across the business. If you are passionate about working with large language models (LLMs), vector stores, and production-grade ML pipelines, this is the role for you.

Key Responsibilities :

- Design, build, and deploy end-to-end ML and generative AI models, ensuring scalability and reliability.

- Develop Retrieval-Augmented Generation (RAG) pipelines integrated with domain-specific data.

- Build and maintain autonomous AI agents using frameworks such as AutoGen, LangGraph, or similar tools.

- Collaborate with cross-functional teams to deploy AI applications on Azure cloud infrastructure (e.g., Azure ML, Web Apps, Azure Search, Foundry etc).

- Fine-tune LLMs for specific business tasks using prompt engineering or model training techniques.

- Work with embedding models, vector databases, and custom knowledge retrieval pipelines.

- Ensure model robustness through MLOps best practices, including version control, CI/CD workflows, and containerized deployments.

- Build APIs and services using frameworks like FastAPI or Flask for serving AI models.

Required Qualifications :

- 4+ years of hands-on experience as a Data Scientist, ML Engineer, or AI Researcher.

- Strong Python programming expertise with proficiency in machine learning and LLM-related libraries.

- Proven experience deploying generative AI and RAG-based systems in production.

- Deep understanding of Azure services, especially Azure Machine Learning, Web Apps, and Functions.

- Strong grasp of RESTful APIs, microservices, and real-time ML inference pipelines.

- Solid experience with vector databases (e.g., Qdrant, FAISS, Chroma etc.)

Preferred Skills :

- Experience with AutoGen, LangGraph, CrewAI, or custom agent frameworks.

- Working knowledge of embedding techniques and semantic search.

- Familiarity with Docker, Git, and CI/CD pipelines for model deployment.

- Exposure to OpenAI, Anthropic, Gemini, Claude, or similar LLM APIs.

Tools & Technologies :

- Languages & Frameworks : Python, FastAPI, Flask

- Cloud : Azure ML, Azure Web Apps, Azure Functions

- LLMs & GenAI : OpenAI, HuggingFace, LangChain, AutoGen, LangGraph

- Vector DBs : FAISS, Pinecone, Chroma, Qdrant

- DevOps & Deployment : Docker, Git, CI/CD (GitHub Actions, Azure DevOps)