Grace Tang is an AI engineer with seven years of experience bridging research and production, currently building at Hex after a stint researching reinforcement learning for dexterous robotic manipulation with Berkeley RAIL under Prof. Sergey Levine. A UC Berkeley EECS and Mathematics graduate, she has interned on quantitative trading teams at Jane Street and PEAK6 and improved backend systems at Roblox, where her rollout cut game update times by over 70% for almost all games. Her work blends rigorous ML research, hands-on systems engineering, and quantitative thinking, with a particular interest in applying RL to real-world robotics and finance problems. Off-hours she sharpens her logical thinking through puzzles and board games and explores creativity through painting, reflecting a rare mix of analytical precision and artistic curiosity.
7 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Electrical Engineering and Computer Sciences, Mathematics, Bachelor of Science - BS, Electrical Engineering and Computer Sciences, Mathematics at UC Berkeley Electrical Engineering & Computer Sciences (EECS)
Contributions:55 pushes, 18 branches in 1 year 8 months
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