At Uber Eats, I work across machine learning services and event-driven backend systems, connecting model outputs with production APIs and data pipelines. I’ve developed RAG pipelines that combine document ingestion, hybrid retrieval, query rewriting, and re-ranking to provide more grounded context for AI applications.
I’ve connected planning, retrieval, and tool execution in agent workflows using LangChain, LangGraph, and AutoGen, with validation and human review for unreliable outputs. My model adaptation work has included LoRA and instruction tuning, with evaluations weighing answer quality, latency, and operating cost.
At EY, I worked on machine learning solutions for enterprise and financial services clients, including document search across policies and knowledge bases. I contributed to NLP projects in classification, information extraction, semantic search, and summarization, while supporting traceability and operational controls for regulated environments.
Earlier, at Coca-Cola and Insilicom LLC, I worked on predictive analytics, backend APIs, data pipelines, and deployment workflows. Across these roles, I’ve connected machine learning features to the applications and operational processes that use them, and have mentored engineers and worked with product, platform, client, and engineering teams.
