New York City Metropolitan Area
Leading the AI training infrastructure team, building and supporting the frameworks (training loops) and many of the key components (TorchRec, Checkpointing, among others) for training massive scale recommendation system models used by Ads, IG, and more. In addition to that, my team builds the key content understanding training frameworks (both "classic" deep learning and LLM post-training/RL) used by every product group at Meta to better understand Ads and content on the platform.
Teaching Applied Machine Learning (Fall) and Intro to Machine Learning (Spring) in the Computer Science department.
Eng Director for Semantic Location in Google Maps, previously Principal Engineer and uber tech lead. Responsible for surfaces like Timeline, place popularity, multi modal transitions (e.g., walk-->train), data provider for many of your favorite Maps features, machine learning (in the cloud and on device), privacy preserving techniques at scale (e.g., federated learning/analytics), and doing more with less signal. Prior to joining Geo/Maps, I was the founding engineer, tech lead, and manager of Google's Enterprise machine learning team, the Corp Eng Machine Learning team. I grew the team and we built and maintained machine learning platforms that make it fast and easy to iterate on classification, clustering, and "nearest neighbor" search. The platform handles configuration, feature extraction, and exposing APIs without needing to write code. My team also interfaced with other teams at Google to build machine learning solutions for product areas such as Legal, Marketing, real estate management, and many others.
Software engineering on GS's strategic post-execution trade processing system which performs trade reporting, figuration, aggregation, explosion, trade confirmation, etc. Primarily focused on regulatory-related aspects of the software. Lead of the SDLC stack in Middle Office. I also manage the release process globally for Middle Office.