Senior Manager, RAG/LLM Specialist

Job description

Job Description: Role Overview: Lead the design and optimization of advanced RAG pipelines and model finetuning processes. Bridge the gap between prototype and enterprise-scale LLM deployment. **Responsibilities: 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/LoRA) 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. - Qualifications: Tech Stack: Python, PyTorch/TensorFlow, LangChain, LlamaIndex, advanced embedding models. - **GenAI Skills:** Deep expertise in advanced RAG (HyDE, parent-document retrieval), prompt optimization, and parameter-efficient fine-tuning. - **Qualifications:** Bachelor’s/Master’s in CS/Data Science with 4–7 years in ML/AI, including 1+ years specifically working with LLMs.