Machine Learning Engineer & Data Scientist
Building production ML systems — from LLM-powered automation to healthcare AI

• 🎓 M.S. Data Science @ Worcester Polytechnic Institute (WPI) | GPA: 3.9/4.0
• 🏆 Best Data Science Project award winner (1st place out of 20+ teams) — healthcare ML project
• 🏥 8+ years building production ML systems across healthcare, fintech, and IoT
• 🤖 Passionate about LLMs, semantic search, and ML pipeline automation
• 📦 Open-source contributor — published 4 Python packages on PyPI
• 📍 USA

• Refund Pilot — Production e-commerce refund agent: deterministic 5-node LangGraph pipeline enforcing a written policy via Claude tool-forcing (temperature=0), SSE streaming, auditable trace dashboard, prompt-injection defense, full OTel→Grafana observability
• LLM-Powered Ticket Routing — Claude API-based system automating 40% of classification workflows, saving ~$700/month in operational costs
• ICD-10 Medical Coding System — Production LLM serving 10+ enterprise healthcare clients, processing 100K+ monthly requests
• Semantic Search Platform — Vector embeddings over 940K healthcare documents, delivering ~$80K/month in operational savings
• ML Document Classifier — Production classifier automating 80% of daily document triage (900+ docs) with 99%+ uptime
• Time-Series Forecasting — PyTorch pipeline predicting equipment failures 30 days in advance
• LoRA Fine-Tuning Pipeline — End-to-end text classification with parameter-efficient fine-tuning and reproducible benchmarking

• Dissecting Agentic RAG: A Component Ablation for Multi-Hop QA with a Local 7B Model — controlled ablation on 5,000 HotpotQA multi-hop questions isolating which agentic-RAG components drive accuracy; fixed hybrid retrieval (RRF) beats rule-based adaptive routing. +10.1 EM / +7.6 F1 for the full agentic pipeline vs. baseline (best single variant EM 55.0% / F1 63.5%), fully local at zero API cost.

AI & ML Frameworks

LLMs & Vector Search

Data Engineering & ETL

Production & MLOps

Languages

• 🏥 Deployed production LLM for ICD-10 medical coding serving 10+ enterprise healthcare clients
• 🔍 Built semantic search over 940K documents, saving ~$80K/month in operational costs
• ⚡ Automated 80% of daily document triage with ML classifier (900+ docs/day)
• 📊 Optimized PySpark ETL for 15M+ Medicare records — 75% fewer data scans, 58% faster queries
• 📦 Published 4 open-source Python packages on PyPI for ML pipeline tooling
• 🏆 1st place — WPI Best Data Science Project (Winter 2024)

💬 Let's connect — always happy to chat about ML engineering, LLMs, healthcare AI, or open-source!