<p><p><b>Job Title : </b> Data Scientist GenAI & : </b> 7 to 10 : </b> Hyderabad / Period : </b> Immediate to 20 Overview : </b></p><p><b><br/></b></p><p>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.</p><p><br/></p><p><b>Key Responsibilities : </b></p><p><br/></p><p>- Design, develop, and deploy AI-driven applications using Python, REST API frameworks like Flask or FastAPI.<br/><br/></p><p>- Build and integrate GenAI/LLM-based solutions using tools such as LangChain, LangGraph, or similar orchestration frameworks.<br/><br/></p><p>- Implement RAG (Retrieval-Augmented Generation) pipelines and optimize prompt tuning strategies including Chain-of-Thought (CoT), Tree-of-Thought (ToT), and Few-Shot Learning.<br/><br/></p><p>- Work with vector databases like FAISS, Pinecone, or Azure Cognitive Search for semantic search and embeddings.<br/><br/></p><p>- Leverage embedding models (e.g., Sentence Transformers, CLIP, SIGLIP) for knowledge retrieval and classification.<br/><br/></p><p>- Optimize performance and scale AI solutions for high payload volumes, manage tokens, and handle long-form data inputs.<br/><br/></p><p>- Integrate and transform structured and semi-structured data formats using schema mapping techniques.<br/><br/></p><p>- Deploy and manage solutions on Microsoft Azure, using services like App Services, Azure Functions, Blob Storage, and Cosmos DB.<br/><br/></p><p>- Use Git and CI/CD pipelines (Azure DevOps or GitHub Actions) for version control and continuous Skills : </b></p><p><br/></p><p>- Advanced Python programming (OOP, asynchronous programming)<br/><br/></p><p>- Experience with REST APIs using Flask or FastAPI<br/><br/></p><p>- Hands-on with Microsoft Azure cloud ecosystem<br/><br/></p><p>- Proficiency in GenAI/LLM orchestration (LangChain, LangGraph, etc.)<br/><br/></p><p>- Familiarity with RAG patterns, prompt tuning, and embedding techniques<br/><br/></p><p>- Strong knowledge of vector DBs and semantic search<br/><br/></p><p>- Experience in scaling GenAI applications<br/><br/></p><p>- Solid understanding of schema transformation for varied data formats<br/><br/></p><p>- Experience with Git, Azure DevOps, or GitHub (Preferred) : </b></p><p><br/></p><p>- Proven experience deploying GenAI applications in production (enterprise environment)<br/><br/></p><p>- Familiarity with AgentOps or MLOps pipelines<br/><br/></p><p>- Exposure to VLLMs or lightweight open-source LLMs<br/><br/></p><p>- Experience with production support / hypercare for live AI systems</p><br/></p> (ref:hirist.tech)