David Feng is a machine learning engineer with 10 years of experience who combines a strong mathematical physics background from the University of Waterloo with hands-on ML and software engineering across startups and large tech. He has built production ML systems for monetization and ranking at Meta and led end-to-end generative AI tooling, MLOps, and ML system design as founding engineer at an AI startup. His career spans fintech, fraud detection, platform engineering, and algorithmic trading, reflecting a knack for applying quantitative methods to messy, real-world data problems. Comfortable across backend, ETL, and distributed systems, he repeatedly ships robust pipelines and tooling that bridge research models to production. Based in New York, he brings both startup grit and product-oriented engineering from early-stage builds to scalable systems at scale. Colleagues would note his uncommon mix of theoretical depth and pragmatic product focus—he’s as likely to derive a model from first principles as to deploy it with CI/CD.
10 years of coding experience
7 years of employment as a software developer
Bachelor of Science Mathematical Physics, Minor in Pure Mathematics, Bachelor of Science Mathematical Physics, Minor in Pure Mathematics at University of Waterloo
Contributions:12 commits, 365 pushes, 3 branches in 4 months
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