
Grid Dynamics
2 days ago
Job Title : Data Scientist GenAI & Azure
Experience : 7 to 10 years
Location : Hyderabad / Bangalore
Notice Period : Immediate to 20 Days
Role Overview :
We are seeking a highly skilled and hands-on Data Scientist with deep expertise in Generative AI (GenAI), Python development, and Microsoft Azure. The ideal candidate will have experience designing and deploying scalable AI/ML solutions using modern GenAI frameworks and orchestration tools. This is an exciting opportunity to work on cutting-edge enterprise-grade AI applications.
Key Responsibilities :
- Design, develop, and deploy AI-driven applications using Python, REST API frameworks like Flask or FastAPI.
- Build and integrate GenAI/LLM-based solutions using tools such as LangChain, LangGraph, or similar orchestration frameworks.
- Implement RAG (Retrieval-Augmented Generation) pipelines and optimize prompt tuning strategies including Chain-of-Thought (CoT), Tree-of-Thought (ToT), and Few-Shot Learning.
- Work with vector databases like FAISS, Pinecone, or Azure Cognitive Search for semantic search and embeddings.
- Leverage embedding models (e.g., Sentence Transformers, CLIP, SIGLIP) for knowledge retrieval and classification.
- Optimize performance and scale AI solutions for high payload volumes, manage tokens, and handle long-form data inputs.
- Integrate and transform structured and semi-structured data formats using schema mapping techniques.
- Deploy and manage solutions on Microsoft Azure, using services like App Services, Azure Functions, Blob Storage, and Cosmos DB.
- Use Git and CI/CD pipelines (Azure DevOps or GitHub Actions) for version control and continuous deployment.
Must-Have Skills :
- Advanced Python programming (OOP, asynchronous programming)
- Experience with REST APIs using Flask or FastAPI
- Hands-on with Microsoft Azure cloud ecosystem
- Proficiency in GenAI/LLM orchestration (LangChain, LangGraph, etc.)
- Familiarity with RAG patterns, prompt tuning, and embedding techniques
- Strong knowledge of vector DBs and semantic search
- Experience in scaling GenAI applications
- Solid understanding of schema transformation for varied data formats
- Experience with Git, Azure DevOps, or GitHub Actions
Nice-to-Have (Preferred) :
- Proven experience deploying GenAI applications in production (enterprise environment)
- Familiarity with AgentOps or MLOps pipelines
- Exposure to VLLMs or lightweight open-source LLMs
- Experience with production support / hypercare for live AI systems
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