Rag / Llm Specialist

Role Overview: Lead the design and optimization of advanced RAG pipelines and model fine tuning processes. Bridge the gap between prototype and enterprise-scale LLM deployment. Key Responsibilities Pipeline Ownership: Design and manage complex, multi-stage RAG pipelines ensuring low latency and high relevance. Model Optimization: Lead fine-tuning initiatives (PEFT/Lo RA) for open-source models to improve domain-specific task performance. Advanced Evaluation: Develop automated evaluation frameworks (e.G., RAGAS) to continually measure LLM accuracy, context precision, and recall. Vector Strategy: Architect metadata filtering and hybrid search strategies within vector databases (e.G., Pinecone, Milvus). Team Mentorship: Guide junior analysts in prompt engineering, chunking strategies, and code quality. Required Skills & Qualifications Tech Stack: Python, Py Torch/Tensor Flow, Lang Chain, Llama Index, advanced embedding models. Gen AI Skills: Deep expertise in advanced RAG (Hy DE, parent-d...