Lucas Ou-yang is a seasoned machine learning engineer and engineering manager with 13 years building recommendation, search, and content-understanding systems at Meta, TikTok, Coinbase, and Snap. He led Coinbase’s recommendation system from inception to significant revenue impact and recently contributed to Meta AI Search work optimizing LLM tool calling and document indexing. An active open-source maintainer, he authored newspaper3k, one of the most-used Python libraries for news scraping and article extraction. Equally comfortable in technical leadership and hands-on ML engineering, he combines deep production experience in RecSys and RAG with a Wharton MBA and a background that spans building core ranking algorithms to publishing on industry differences between US and Chinese firms. He is based in Los Angeles and consults on scraping, recommendation systems, and retrieval-augmented generation.
13 years of coding experience
8 years of employment as a software developer
University of California, Irvine
University of Pennsylvania
Skyline High School
Master of Business Administration - MBA, Master of Business Administration - MBA at The Wharton School
newspaper3k is a news, full-text, and article metadata extraction in Python 3. Advanced docs:
Role in this project:
Back-end Developer
Contributions:458 commits, 145 PRs, 221 pushes in 6 years 10 months
Contributions summary:Lucas's primary contributions focused on the initial setup and architectural design of the "newspaper" project, including foundational files like `source.py`, `setup.py`, and `api.py`. The user implemented the core structure by establishing classes and methods for essential components such as `Source`, which encapsulates a news domain, and `Article`. The commits also establish API functionality, and define the core structure.
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