MS CS (AI/ML) — Northwestern '24 | Currently: AI/ML Engineer
Building real-time voice AI pipelines (sub-800ms latency) and RAG systems at Bhuvi IT. Previously shipped distributed 8-GPU training at Argonne National Lab (2TB astronomical data, 1 week → 20 hours) and graph-based entity resolution (0.96 F1) as standalone projects. Comfortable across the full stack from model training to serverless cloud deployment.
Open to ML Engineering, Applied AI, AI Infrastructure, Software Engineering or Data Scientist roles.
buvanipai · · focus · HN ↗
Remote: Yes
Willing to relocate: Open to Remote, Hybrid, and In Person roles
Technologies: Python, PyTorch, LangChain, FastAPI, ChromaDB, PostgreSQL, Docker, Google Cloud Run, AWS, GCP, React.js, SQL, spaCy, NetworkX
Résumé/CV: <a href="https://buvanipai.vercel.app/Buvani_Pai_Resume.pdf#view=FitH" rel="nofollow">https://buvanipai.vercel.app/Buvani_Pai_Resume.pdf#view=FitH
Portfolio: <a href="https://buvanipai.vercel.app/" rel="nofollow">https://buvanipai.vercel.app/
Email: buvanipai@gmail.com
MS CS (AI/ML) — Northwestern '24 | Currently: AI/ML Engineer
Building real-time voice AI pipelines (sub-800ms latency) and RAG systems at Bhuvi IT. Previously shipped distributed 8-GPU training at Argonne National Lab (2TB astronomical data, 1 week → 20 hours) and graph-based entity resolution (0.96 F1) as standalone projects. Comfortable across the full stack from model training to serverless cloud deployment.
Open to ML Engineering, Applied AI, AI Infrastructure, Software Engineering or Data Scientist roles.