I lead 20 engineers across 4 teams in Meta’s Business & Creator Monetization org:* Hired new team to launch Short Form Video ( Reels ) Ads Ranking stack, a key company strategic priority, and delivered 34% revenue improvement over baseline models in 2022* Hired & led teams for Watch Ads Ranking and Stories Ads ranking, driving 6% and 17% revenue improvement YoY* Increased Feed Ranking performance for Content Creators & Live Gaming segments, driving up paid subscriptions by 4% and tips by 5% in 6 months* Created v-team to automate ads anomaly detection to enable company-wide upgrade from legacy Pages data models to a new Profile+ offering, unlocking a new experience for hundreds of millions of Creators & Biz segments, and helping mitigate a 9% ads revenue regression due to legacy feature incompatibilities* Led Model Lifecycle automation team, using automated model exploration techniques to automatically upgrade 25% of Facebook Ads models with newer features, techniques, and hyperparameters.

Org size: 3 engineering teams (15 eng) + 125 ML-OpsI created and grew a multi-team, catalog quality program that uses Generative AI to power 30% of Amazon’s structured metadata, impacting 12B+ eCommerce products across 20 languages:Scaled the program: from a proof of concept stage to powering 30%+ of Amazon’s catalog metadata, using 25k state-of-the art deep learning models. Models span a variety of techniques, from classical machine learning, few-shot learning, transformers, LLM, and Generative AI to automatically creating clean, structured metadata for thousands of categories, dozens of languages, and over 13+ billion eCommerce products* Defined charter, hired, and grew three engineering teams (one Applied Science team, one ML Engineering team, and one ML Infrastructure team)* Defined and scaled 125+ ML-Ops org, responsible for working across Amazon business verticals, owning model lifecycle management, human-in-the-loop data collection, metrics, and multi-year company initiatives. * Interviewed 800+ candidates, and defined hiring standard processes across VP-level org (2k people) spanning 10 unique job classifications from engineering, applied science, project management, to ontology.

I manage a full-stack team of 5-10 engineers chartered with building data-driven features Amazon.com's Search. We blend expertise in data mining, machine learning, and highly-scaled services with native web & mobile skill, and solve search problems for customers shopping in all categories around the globe.

I manage a small, flexible team of software developers inside the Personalization group at Amazon.com. Our mission: build knowledge and understanding of people and things into Amazon systems. In 2013, we're going to start understanding our users better than ever.We mine a variety of data sources, both inside and outside the company, to build authoritative knowledge of topics and the relationships between them. We use machine learning, natural language processing, semantic web, and cloud computing to tackle ambiguous problems at huge scale.

I develop the underlying systems that power Amazon Video on Demand. It's a broad space, so I write code to handle asset reception, encoding, catalog systems, and content playback (everything from computers to TVs and connected devices.)Most code is in java in a services-oriented-architecture, with an emphasis on scalability.

Lotus NotesJavaRuby on RailsUI Design Lead