Data Scientist

Required Qualifications: Experience in software engineering or data science, with in Gen AI or LLM-based systems. Strong Python programming skills and experience with ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch). Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search). Familiarity with cloud platforms and Gen AI services (AWS, Azure, GCP). Experience with REST API development (FastAPI, Flask) and containerization (Docker). Solid understanding of AI governance, model safety, and prompt engineering.

Key Responsibilities: Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI). Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT. Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search. Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI). Work with unstructured data (PDFs, HTML, audio, images) and multimodal models. Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking. Evaluate model performance using tools like RAGAS, DeepEval, and FMeval. Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions.