Brent Payne is a seasoned machine learning leader with 14+ years of experience building production personalization systems, currently opening and managing ML applications teams in NYC and Seattle for Amazon. He blends hands-on engineering roots—evidenced by open-source contributions optimizing core Node.js stream primitives—with strategic product leadership from co-founding ML-forward startups and leading ML teams at ad-tech and B2B companies. Brent's career spans research, systems engineering, and go-to-market pivots, giving him a rare fluency in turning ML research into scalable, user-facing recommendations. He holds an M.S. in Artificial Intelligence from UCSD and is known for tackling performance and edge-case robustness in both legacy and modern runtime environments.
14 years of coding experience
13 years of employment as a software developer
University of California San Diego
Johns Hopkins University
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at University of Kentucky
High-level streams library for Node.js and the browser
Role in this project:
Back-end Developer
Contributions:12 commits, 1 PR, 22 comments in 1 month
Contributions summary:Brent primarily focused on optimizing and refactoring the `pick` and `pickBy` methods within the `highland` streams library. They reduced the runtime complexity of these methods and reimplemented them using more efficient techniques like `map` and `curry`. The user also addressed edge cases by updating tests and handling non-enumerable properties. Furthermore, they updated the code to work correctly in both ES5 and ES3 environments.
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.