Summary
James Gabriel is a Senior Machine Learning Engineer in Seattle with a decade of experience bringing efficient, edge-ready AI to production at companies from startups to Apple. His background blends deep research—designing novel CNN architectures, layers, and losses for resource-constrained devices—with hands-on systems work in robotics, computer vision, and mechatronics from Intel and Carnegie Mellon. He led prosthetics development in CMU’s Biomechatronics Lab and has practical product design experience from roles at Stanley Black & Decker and 4moms, giving him a rare mix of rigorous math, firmware-aware optimization, and real-world engineering. At XNOR.AI he focused on squeezing deep learning into tiny devices; at Apple he now applies that expertise at scale, optimizing models for edge deployment. Colleagues describe him as someone who dives into mathematical foundations yet keeps one eye on manufacturability and power budgets—making cutting-edge models actually work on constrained hardware.
10 years of coding experience
7 years of employment as a software developer
Landon
Master's degree, Robotics, Master's degree, Robotics at Carnegie Mellon University
BSE, Biomedical Engineering, BSE, Biomedical Engineering at Duke University Pratt School of Engineering
English, Chinese