Tsan-chen Li is an AI/ML software engineer with eight years of experience building full-stack systems and production ML infrastructure, currently on Siri at Apple. He combines rigorous academic training from Carnegie Mellon and Zhejiang University with hands-on experience across backend services, AWS, computer systems, web frontend, and iOS. Past roles include developing load-balancing job schedulers at NVIDIA and migrating supply-chain logic to cloud-native stacks at Apple, reflecting a practical focus on scalability and cost-efficiency. As a visiting researcher at MIT he contributed computer vision and depth-imaging solutions for medical and robotic applications, showing an ability to translate research prototypes into real-world impact. Based in the Bay Area, he pairs strong systems engineering with ML experimentation, and unusually for his profile, brings formal statistics training to inform model design and evaluation.
8 years of coding experience
1 year of employment as a software developer
Exchange Semester, Informatics, 3.60 / 4.00, Exchange Semester, Informatics, 3.60 / 4.00 at Technical University Munich
Master’s Degree, Mobile and IoT Engineering, 4.00 / 4.00, Master’s Degree, Mobile and IoT Engineering, 4.00 / 4.00 at Carnegie Mellon University
Bachelor of Engineering - BE, Computer Science and Technology, 3.63 / 4.00, Bachelor of Engineering - BE, Computer Science and Technology, 3.63 / 4.00 at Zhejiang University
A Command Line Interface (CLI) for Spotify built using Rust, where users can manage their Spotify songs and playlists through the Command Line
Contributions:1 release, 28 pushes, 5 branches in 2 months
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