Shengmin Z is a machine learning engineer with five years of experience building data-driven models and production ML systems across fintech and HR platforms. He holds a Ph.D. in Physics and transitioned from quantitative risk modeling at BNY Mellon to data science roles at Capital One and Gusto, now applying ML at ByteDance. His background blends rigorous research training with practical experience in deploying robust models in regulated and high-scale consumer environments. Comfortable at the intersection of statistics, engineering, and product, he has repeatedly moved from prototype to production in cross-functional teams. Based in McLean, Virginia, he brings both domain depth in financial risk and curiosity-driven problem solving uncommon in typical ML practitioners.
5 years of coding experience
6 years of employment as a software developer
Bachelor's degree Physics, Bachelor's degree Physics at University of Science and Technology of China
Doctor of Philosophy (Ph.D.) Physics, Doctor of Philosophy (Ph.D.) Physics at University of Pittsburgh
UME is an in-app debug kits platform for Flutter. Produced by Flutter Infra team of ByteDance
Contributions:8 pushes, 1 branch in 4 days
umebackground-servicedartinfrateam-infra
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Shengmin Z - Machine Learning Engineer at ByteDance