Grid Dynamics - Data Scientist - Generative AI

Job Title : Data Scientist GenAI & : 7 to 10 : Hyderabad / Period : Immediate to 20 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 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 (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

(ref : hirist.tech)