Hudson Ayers is a Senior Software Engineer with eight years of experience building secure embedded systems and platform OS infrastructure for autonomous robotics and automotive companies. Currently on Zoox’s Robot Software Infrastructure team after a stint at Cruise, he focuses on low-level platform reliability, wireless stacks, and memory-efficient embedded Rust. His PhD work at Stanford and multiple Google research internships inform a pragmatic approach to real-time guarantees, kernel-level testing, and flash/memory optimization for constrained devices. An active open-source contributor, he has made substantial changes to the Tock secure embedded OS and helped add adaptive streaming features to Stanford’s Puffer live-TV project. Based in San Francisco, he combines systems research rigor with production engineering, often favoring Rust for safety and performance. A less obvious strength: he bridges academic verification techniques with hands-on driver and wireless stack ports, turning formal insights into deployable embedded software.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Electrical and Computer Engineering Dual Major, Bachelor of Science - BS, Electrical and Computer Engineering Dual Major at University of Virginia
Enloe High School
Doctor of Philosophy (Ph.D.), Electrical Engineering, Doctor of Philosophy (Ph.D.), Electrical Engineering at Stanford University
A secure embedded operating system for microcontrollers
Role in this project:
Embedded Systems Engineer / IoT Developer
Contributions:1 release, 1913 reviews, 586 commits in 5 years 4 months
Contributions summary:Hudson primarily contributed to the implementation and improvement of the Tock operating system on microcontrollers, focusing on the IEEE 802.15.4 wireless communication stack. They were responsible for porting drivers and modifying the low-power kernel functionality. The user also developed kernel-level tests to verify correct packet handling and other system aspects. Their work included addressing issues related to memory management and the correct use of Result in HIL functions.
Puffer is a free live TV streaming website and a research study at Stanford using machine learning to improve video streaming
Role in this project:
Full-stack Developer
Contributions:152 commits, 2 PRs, 114 pushes in 1 year 5 months
Contributions summary:Hudson implemented new features and made significant changes to the frontend and backend of the Puffer project. They added the ability to select different ABR algorithms for video streaming, impacting the core functionality of the live TV streaming website. The user also worked on UI improvements, including an improved index page and the addition of a debug button with additional information. Furthermore, the user refactored the channel selection to use javascript.
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.