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Shreyansh Bhalani
Mid-level Full-Stack & ML Engineer specializing in AI SaaS, MLOps, and cloud infrastructure
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About
Built and shipped an AI-powered driver ranking/assignment system at AffirmoAI using LLM intent classification + RAG over pgvector/Postgres, served via FastAPI with a React UI that explains scores. Drove measurable improvements through optimization and iteration (latency down to <800ms, adoption 60%→90%+) and implemented rigorous eval loops with dispatcher ground truth plus cold-start handling for new drivers.
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Key Strengths
- Shipped production LLM+RAG system end-to-end (FastAPI backend + React UI) for driver ranking with explanations
- Performance optimization via caching and reduced feature set (3–4s to <800ms / ~700ms) while maintaining 85%+ accuracy
- User-feedback-driven iteration (added route preference learning; adoption improved from 60% to 90%+)
- Built evaluation loop with 200+ real scenarios, dispatcher ground truth, and weekly human reviews
- Solved cold-start problem for new drivers (<10 deliveries) with alternate weighting + similar-profile retrieval (accuracy 60%→78%)
- Designed scalable messy-data pipeline with normalization, retries, validation, observability; scaled 50→500+ deliveries/day while cutting geocoding API calls 80%
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