John Carter
Founding Engineer at Generalist AI
Upton, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolJohn Carter is a founding engineer and robotics autonomy specialist with 11 years of experience delivering high-performance autonomy across industry and academia, including technical lead roles on high-profile DARPA programs. He has led system architecture, planning, mapping, and simulation efforts for autonomous quadrotors and humanoid robots, and shipped production-grade autonomy at companies from MIT to Zoox and startups he founded. A hands-on software engineer, he contributes low-level robotics code (notably to Drake) focusing on contact dynamics, simulation, and Windows-compatible tooling—skills that bridge research prototypes and fielded systems. Based in Upton, MA, he combines deep algorithmic expertise with pragmatic engineering, having served as both safety pilot in field tests and a founder building AI-first products.
11 years of coding experience
9 years of employment as a software developer
University of California, Los Angeles
Github Skills (6)
c-language10
robotics10
eigen10
cprogramming-language10
linear-algebra9
numerical-optimization8
Programming languages (8)
Github contributions (5)
RobotLocomotion/drake
Jan 2015 - Mar 2016
Model-based design and verification for robotics.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 374 commits, 95 PRs in 1 year 1 month
Contributions summary:John primarily worked on implementing and improving low-level code, specifically related to robotics applications. They implemented and debugged a mex interface for computing friction cone surface tangent basis vectors, including fixes for Windows compatibility and type incompatibilities. The contributions involved modifying various plant systems related to contact constraints, and a test framework to improve these constraints within the Drake framework, demonstrating a focus on functionality and optimization related to robotics.
roboticsdrake
psiorx/Reinforcement-Learning
Jul 2017 - Feb 2019
Simple C++ project that includes header only implementations of Monte Carlo Tree Search(MCTS), Temporal Difference Learning, Minimax, and other agents to evaluate their performance in various two player games.
Contributions:60 commits, 2 PRs, 13 pushes in 1 year 7 months
cppminimaxmonte-carlotemporal-difference
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