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Bill Zoheb
Senior AI Engineer specializing in LLMs, RAG, and production ML systems
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Built GynAI, an end-to-end maternal clinical decision support platform for OB/GYN practices and hospitals in North America, combining predictive ML with RAG-based LLM explainability. The candidate emphasizes real production ownership across experimentation, deployment, monitoring, and iteration, with reported impact including fewer delayed interventions in high-risk pregnancies and a 15-20% reduction in false positives.
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Key Strengths
- owned an end-to-end production healthcare AI system
- applied ML to maternal clinical decision support
- built RAG-based clinician explainability on top of risk models
- strong production ML operations: monitoring, drift, latency, experiment logging
- handled noisy and incomplete clinical data with preprocessing and validation layers
- improved model precision by reducing false positives 15-20%
- drove reduced delayed interventions in high-risk pregnancies
- optimized LLM systems for latency and cost using smaller models, retrieval tuning, and Redis caching
- standardized shared Python/ML APIs across teams
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