Trevor Phillips is a Machine Learning Engineer based in Zurich with 11 years of experience applying ML to challenging 2D/3D computer vision problems and production systems. He blends research-grade expertise in depth estimation and real-time reconstruction—proven by a NASA JPL project achieving ~1% depth error—with hands-on deployment experience at Apple and PXL Vision building end-to-end ML pipelines and privacy-aware data flows. His interests span combinatorial and convex optimization, including semidefinite relaxations applied to cryptographically hard problems, giving him a strong theoretical edge when tackling ill-posed vision and optimization tasks. Comfortable across C++, Python, ROS and modern ML stacks, he has a track record of improving prototype velocity and operational robustness in cross-functional teams. Known for practical engineering (e.g., Kalman filters for GPS, tooling to speed developer workflows), he pairs academic rigor from ETH Zürich with product-focused delivery.
11 years of coding experience
3 years of employment as a software developer
Bachelor’s Degree, Computer Science and Engineering, 3.98, Bachelor’s Degree, Computer Science and Engineering, 3.98 at University of Connecticut
Master of Science - MS, Robotics, Systems, and Control, Master of Science - MS, Robotics, Systems, and Control at ETH Zürich
Contributions:67 commits, 33 PRs, 77 pushes in 1 month
javaparking
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Trevor Phillips - Machine Learning Engineer at Apple