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Chien-Ting Hung
Director-level AI Engineer specializing in computer vision and LLM/RAG platforms
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About
Hands-on LLM/RAG engineer with production experience improving retrieval quality and stability by addressing messy data, vector DB inaccuracy, and top-K issues—ultimately redesigning to hybrid search with tuned keyword/semantic weighting and MCP-based data supplementation. Also brings strong AKS/Kubernetes deployment experience, optimizing CI/CD speed via lightweight local Docker validation and decomposing pods to avoid full rebuilds, plus a metrics-driven approach to agent/workflow testing and traceability.
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Key Strengths
- Deep practical RAG troubleshooting (data quality, top-K behavior, retrieval accuracy)
- Improved retrieval accuracy by redesigning to hybrid search and tuning keyword/semantic weighting
- Performance optimization under load (index adjustments; dynamic top-K to manage query latency)
- Production-minded MLOps/infra experience with Docker, Kubernetes, and AKS
- Reduced deployment time by creating lightweight local Docker test environment and splitting pods to avoid full rebuilds
- Systematic agent reliability approach (explicit tool-call decisions, traceability, E2E tests incl. failure recovery, metrics + fallback tracking)
- Effective cross-functional collaboration with business stakeholders using value framing, visualization, and user-involved testing feedback loops
Reference Highlights
- Led AI team responsible for end-to-end architecture and development
- Thorough design process informed by market trends/frameworks
- Strong cross-functional communication with PM team
- Drives consensus in communications
- Able to make complex concepts easy to understand using visuals and examples
- Ensures releases occur only after testing verification
- Responsible
- Knows what he is doing
- Proactive in learning (reads AI papers to solve issues)
- Open to discussion
- Patient with non-technical stakeholders
- Explains technical issues clearly
- Uses examples/demonstrations to aid understanding
- Able to overcome technical hurdles (improved OCR accuracy through tuning)
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