I'm a Data Science master's student at UC Irvine, graduating December 2026, with a computer science background from VIT. My work sits where machine learning, large language models, and the data engineering that makes them reliable all meet.
During my internship at Quantiphi, I worked in a six-person team building a production RAG support-assist tool on Google Cloud, contributing to the retrieval pipeline, data preparation, and the evaluation harness that gated every release. I learned that the hard part of applied AI is rarely the model, it's the measurement, the grounding, and the plumbing around it.
Outside of work I build projects across the parts of AI I find most interesting: agentic RAG, cost-aware LLM routing, streaming anomaly detection, and recommender systems, always with an emphasis on evaluation and honest metrics.
A selection of projects spanning LLM systems, ML engineering, and analytics. Each links out to the code or a live demo.
I'm open to full-time Data Science, ML Engineering, and Applied AI roles. The best way to reach me is email.