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silin liu
Mid-level AI/ML Engineer specializing in LLM agents, RAG, and enterprise ML systems
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Built a production multi-agent recommendation/RAG system for internal data analysts to speed up weekly report creation by improving document discovery and automating report/SQL generation. Implemented LangGraph-based orchestration with deterministic agent routing, robust error handling (interrupt/resume), and metadata-driven semantic chunking for diverse PDF/document formats, plus monitoring for latency, throughput, and token/cost efficiency.
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Key Strengths
- Built and deployed a multi-agent recommendation/RAG system to reduce analyst time spent finding documents for weekly reporting
- Designed agent workflows as a graph-structured state machine with deterministic routing, error handling, and interrupt/resume support
- Handled heterogeneous document formats (including PDFs) using format filtering and semantic chunking with metadata-aware retrieval
- Implemented hybrid retrieval using a vector database (Chroma) combining semantic search with keyword mapping
- Established production monitoring for latency/throughput and token/cost efficiency using tracing and caching/embedding optimizations
- Effective stakeholder collaboration via iterative demos and production stability evidence (logs, error handling over 1–2 weeks)
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