AI/ML Engineer building production RAG systems, agentic workflows, and data pipelines that turn research into real-world impact. I combine statistical rigor from public health with modern ML infrastructure to ship reliable, scalable AI tools.
- EpiTrends: Real-time public health trend analyzer using NLP and FastAPI microservices, processing 50K+ records/day with 50% faster insight generation
- Health Chatbot: Agentic RAG system with LangChain + Pinecone, delivering 40% more accurate nutrition guidance via semantic retrieval
- QA Automation Suite: Python-based testing pipelines reducing manual validation time by 60% for data preprocessing workflows
- Contributing TypeScript UI components to BetterAuth with 100% type coverage
- Partnering with healthcare developers to deploy fair, interpretable ML models for public health use cases
- Advanced NLP: Transformers, Hugging Face, retrieval-augmented generation
- MLOps: Containerized deployment with Docker, CI/CD via GitHub Actions, monitoring with Prometheus
- Data storytelling: Power BI, Matplotlib, and Streamlit for actionable public health insights
Languages: Python | TypeScript | SQL | Bash
AI/ML: LangChain | RAG Pipelines | PyTorch | scikit-learn | Prompt Engineering
Backend: FastAPI | Node.js | REST | Microservices | ETL
Infra: Docker | GitHub Actions | Supabase | Pinecone | FAISS
Frontend: React | Next.js | Streamlit | Tailwind
Open to remote collaborations on AI for social impact, production LLM systems, and developer tooling.