Baekjin Kim
Machine Learning Engineer, Tech Lead at Snap Inc.
Ann Arbor, Michigan, United States
Summary
👤
Senior🎓
Top SchoolBaekjin Kim is a Machine Learning Engineer and tech lead with a decade of experience blending rigorous statistical research and production ML for ad ranking and monetization. A STAT PhD candidate at the University of Michigan, he focuses on online learning and bandit theory under non-stationary, corrupted, and delayed settings, with a particular interest in randomized algorithms and recent work in differential privacy and RL theory. He has shipped ML systems at scale across Snap, Twitter, and Moloco, bringing research-grade methods into real-time recommendation and ads ranking pipelines. Previously an ML intern at Twitter and a long-time teaching assistant and researcher, he pairs deep theoretical expertise with hands-on engineering and mentorship. Based in Ann Arbor, he often explores intersections between provable sequential decision-making and practical, privacy-aware ML in production.
10 years of coding experience
8 years of employment as a software developer
Master of Science (M.S.), Statistics, Master of Science (M.S.), Statistics at Seoul National UniversityDoctor of Philosophy (PhD), Statistics, Doctor of Philosophy (PhD), Statistics at University of Michigan
English, KoreanGithub contributions (5)
baekjin-kim/NonstationaryLB
May 2020 - Dec 2020
Contributions:15 commits, 12 pushes, 1 branch in 6 months
baekjin-kim/Perturbation-Methods-StochasticMAB
Apr 2019 - Jun 2020
Contributions:11 pushes, 1 branch in 1 year 1 month
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