Experience

Built from scratch an optimized full-stack testing system for ML models that configure prices for all Amazon Basics items. System now serves as the primary testing framework used by the Base Pricing team for ML model evaluations. Deployed system to production, reducing manual validation time from 12 mins to 2 mins.

Fixed critical memory leaks in satellite controller system code, increasing information transmission efficiency by 24%. Reduced overall system downtime and increased satellite communication stability using Julia.

Wrote algorithms to enhance confidence scoring mechanisms in large-scale language models (15% reliability increase). Implemented rigorous evaluations on confidence scoring code- built benchmark prompt dataset for model testing.

Led a team of 18 developers in creating a self-learning AI SaaS product that generates 3D animated movies from user-submitted scripts. Reduced the CTO's timeline from 6 months to 2 months, Project was acquired by Disney.

Led the creation of a convolutional neural network model for image classification, integrating BERT encoders and decision trees into the architecture. Final product implemented by large health insurance providers, such as Humana and Aetna.

Co-founded under Harvard Innovation Labs, led development efforts using Unity for the frontend and C++ for the backend. Developed platform from the ground up, grew user base from 0 to >127,000 active users. (acquired by Harvard University)