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Duncan Freeman
Staff Machine Learning Engineer specializing in NLP, LLMs, and document intelligence
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About
ML/AI engineer at PNC who has shipped enterprise-grade RAG and document intelligence systems for compliance and policy workflows. Stands out for combining LLM product thinking with production rigor—owning FastAPI/Kubernetes deployments, monitoring, evaluation, and human-feedback loops that drove measurable gains like 40% faster policy search and 30% faster compliance review.
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Key Strengths
- Owned production ML/AI systems end-to-end from prototype to deployment and monitoring
- Strong enterprise RAG architecture for compliance and policy workflows
- Built human-feedback retraining loops to improve retrieval quality and catch regressions
- Balanced latency, cost, quality, and safety in production LLM systems
- Designed grounded summarization with citations and human-review safeguards
- Built reusable Python/FastAPI service libraries adopted across teams
- Improved policy search time by about 40%
- Delivered compliance review workflow that was 30% faster
- Strong evaluation mindset using offline metrics plus human-reviewed production feedback
- Reliable platform engineering with Docker, Kubernetes, contract tests, and staged rollouts
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