Taewon Kim is a machine learning engineer at Meta with 11 years of experience building scalable ML and high-performance systems, currently focused on ads recommendation at scale. He previously architected high-throughput, low-latency DDoS detection and mitigation systems at AWS that processed TB/s data streams and cut time-to-response from 20+ minutes to three. With a PhD in Quantum Chemistry and a strong academic record, he has applied ML, graph algorithms, and numerical optimization to accelerate molecular simulations and design linear-time recommendation and clustering methods for large biological and chemical datasets. He has led interdisciplinary teams to produce widely used open-source scientific libraries and terabyte-scale databases, pairing production-grade DevOps with research-grade rigor. Comfortable translating complex science for general audiences, he bridges research and production to turn advanced models into operational systems. Based in Florida, he brings a rare combination of deep scientific training, systems engineering, and hands-on experience across cloud, HPC, and ML production.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Quantum Chemistry, Doctor of Philosophy - PhD, Quantum Chemistry at McMaster University
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Ghent University
Python library for Gaussian basis function evaluation & integrals
Contributions:148 pushes, 69 branches in 5 months
python-librarypythonevaluationintegralssvd
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