Summary
Kuangzheng Li is a Machine Learning Engineer with nine years of experience specializing in AI, deep learning, and reinforcement learning, currently driving recommendation and production ML systems at hireEZ in Redwood City. He co-authored an IJCAI 2019 paper on expert-level game AI and has built advanced game-playing agents using residual networks, LSTM, Monte Carlo methods and custom probabilistic tree search. At hireEZ he cut latency by 90%, boosted recommendation ranking with XGBoost pairwise models, and automated online/offline evaluation while slashing ML server compute by 80%. Previous roles include an IBM internship where he tuned BERT with reinforcement learning to reduce language drift and designed evaluation workflows for AI–human communication. He combines strong math training (MS degrees from RPI and USTC) with hands-on deployment experience in TensorFlow, AWS, Python and SQL, and a knack for finding low-level API optimizations that yield large resource savings. An engineer who moves from research to scalable production, he balances algorithmic creativity with measurable business impact.
9 years of coding experience
3 years of employment as a software developer
Master's degree Mathematics, Master's degree Mathematics at University of Science and Technology of China
Master of Science - MS Information Technology & Web Service, Master of Science - MS Information Technology & Web Service at Rensselaer Polytechnic Institute
Bachelor's degree Applied Mathematics, Bachelor's degree Applied Mathematics at Ocean University of China
Exchange Student Applied Mathematics, Exchange Student Applied Mathematics at Xiamen University