Samuel Kwong is a Software Engineer III based in San Francisco with eight years of experience specializing in multimodal and planner ML for autonomous vehicles. At Waymo he architects and trains production-scale onboard models for world encoding, trajectory decoding, and multi-task behavior prediction that enable mapless driving and expansion into complex territories like San Francisco. He has a strong research-to-production track record—moving next-gen neural modeling from internship research into deployed systems that handle long-tail agent behavior and pullover/control decisions. A Stanford MS/BS in Computer Science and past roles in cloud ML and computer vision give him deep expertise across perception, prediction, and scalable model deployment. Colleagues would note his blend of rigorous academic grounding and pragmatic engineering that turns foundation world-model research into mission-critical AV software.
8 years of coding experience
4 years of employment as a software developer
Henry M. Gunn High School
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Stanford University
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