Role Overview: Lead the design and optimization of advanced RAG pipelines and model fine[1]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/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.