Kun Fang is an AI engineer and full-stack J2EE cloud application developer with 11 years of experience building scalable systems across major tech firms. He has progressed from principal engineering at Oracle to software engineering roles at Google and Meta, and now focuses on AI engineering in Bellevue. His background in operations research and industrial engineering (Cornell, HKUST, UC Berkeley) gives him a strong foothold in applied optimization and systems thinking that informs both backend architecture and ML-driven features. Known jokingly on GitHub as a "robot trainer and robot trainer trainer," he blends practical engineering with a taste for automation and model training workflows. Colleagues rely on him to translate complex requirements into reliable, production-ready services that bridge cloud platforms and AI components.
11 years of coding experience
9 years of employment as a software developer
Undergraduate, Industrial Engineering and Operations Research, Undergraduate, Industrial Engineering and Operations Research at University of California, Berkeley
Master of Engineering (M.Eng.), Operations Research, Master of Engineering (M.Eng.), Operations Research at Cornell University
Hong Kong University of Science and Technology (HKUST)
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