Summary
Trevor Gordon is a software engineer with 11 years of experience combining electrical engineering rigor with machine learning and reinforcement learning expertise. He holds an MS in Electrical Engineering from Columbia and contributes to RL research on dynamic spectrum access while working as a Software Engineer at Google. Previously he built motion-sensing hardware at Apple and developed firmware, data pipelines, and automated test systems across roles at Tesla, D-Wave, and startups, giving him a strong hardware-to-software systems perspective. Proficient in Python and C++ and comfortable with ML toolchains, he excels at turning complex sensor and time-series problems into production-ready solutions. A not-obvious strength is his history of applying EM and superconducting simulation skills to practical instrumentation problems, reflecting deep physical modeling alongside software delivery.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Applied Science (B.A.Sc.), Electrical and Electronics Engineering, Cumulative GPA: 90% / Major GPA 92%, Bachelor of Applied Science (B.A.Sc.), Electrical and Electronics Engineering, Cumulative GPA: 90% / Major GPA 92% at The University of British Columbia
Master of Science - MS, Electrical Engineering - ML Focus, Master of Science - MS, Electrical Engineering - ML Focus at Columbia University in the City of New York
English