Resume

• Driving GenAI innovation and business transformation, in association with Palantir, across industries — on a portfolio encompassing the LA Dodgers, Lakers, Guggenheim Investments, Group 1001 Insurance, Cadillac Formula 1, etc.
• Embedded with lawyers, investment bankers, and asset managers where I understand how they work, and design custom agentic workflows based on their needs.
• Working on pushing the limits of agentic capabilities, scaling to hundreds of tools, long term memory, and agentic RAG/document understanding over millions of documents, all while maintaining latency SLAs.

• Working with the Audit and Assurance group to help accelerate audit processes using generative AI applications. Implementing long term memory for chat agents, along with fine tuning using RL for more efficient function calling and tool usage.
• Deployed Deloitte's flagship GenAI chatbot for audit professionals — DARTbot / Research Assistant.
• Benchmarked LLM tools like Llamaindex, Langchain, etc. and vector DBs like Chroma, Milvus, Pinecone, etc. for production use cases.

• As a founding ML engineer, I led the development of an AI/ML Governance platform that enables customers to use the latest LLM services/applications with the assurance of enterprise grade compliance and safety policies.
• Built and scaled RAG (Retrieval Augmented Generation) pipelines, along with spearheading AI safety research.
• Optimizing LLM inference and deployment using techniques like model pruning, quantization, and CUDA kernel optimizations.

• Deployed end-to-end pipeline for detecting contradictory statements (NLI) in clinical trial protocol documents using generative AI.

• Led efforts in propensity modeling, market segmentation, and linear optimization for leading bio-pharma clients using EMR and insurance claims data; used explainable algorithms like SHAP, LIME to automate model output explanations from models like XGBoost, Random Forests; expanded project scope to cater to three varied drug portfolios.
• Designed nationwide transportation optimization platform using agent-based simulation for a premier Japanese pharma client, creating a solution for transport scenario simulation, using geo-spatial ML algorithms for optimal treatment center identification.

• Applied deep learning for segmentation/attribute extraction from fashion image datasets and developed a data labeling tool for SMEs.

• Deep learning-based financial forecasting, integrating time-series ensemble methodologies to enhance forecasting accuracy.

Master's degree (MS), Applied Data Science · GPA 3.96 / 4

• Coursework: NLP, Biostatistics, Computer Vision, Quantum Computing, Remote Sensing, Database Design, Cloud Computing.
• Research Assistant: fine-tuning LLMs as part of a pipeline to extract adverse drug event data from clinical trial notes.
• Research Assistant: evaluating and improving gender/ethnicity based bias detection and mitigation algorithms to make LLMs safer.
• Research Assistant: designed and 3D-printed lab containers using Autodesk GenAI and constraint optimization tools — decreased wastage by 30%.
• Teaching Assistant: 2D Animation, Advanced 2D Animation, Motion Graphics.

Bachelor's degree (BS), Computer Science and Engineering · GPA 3.8 / 4