Philip Potter
Member Of Engineering - Infrastructure at poolside
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolPhilip Potter is an infrastructure-focused software engineer with 15 years' experience building reliable systems for government and startups, currently a Member of Engineering - Infrastructure at poolside. He has led platform and SRE efforts at the Government Digital Service and scaled inference infrastructure at Replicate, combining operational rigor with backend engineering and test automation. A Cambridge computer science first-class graduate, Philip blends low-level embedded work—contributions to MicroPython adding USB HID support—with cloud-native infrastructure improvements such as OpenAPI and concurrency fixes in Cog. He is comfortable across languages and stacks (Python, Clojure, C/embedded), and has a strong track record improving test suites and refactoring for maintainability. Colleagues value him for practical, production-first solutions that reduce flakiness and race conditions while keeping systems observable and secure. He brings a pragmatic curiosity—equally at home debugging USB endpoints as optimizing ML container runtimes.
15 years of coding experience
12 years of employment as a software developer
Bachelor of Arts - BA, Computer Science, First class, Bachelor of Arts - BA, Computer Science, First class at University of Cambridge
Github Skills (37)
container10
usb-hid10
docker10
py10
python10
clojure-cli10
dhall10
usb10
c1110
microcontroller10
dockers10
clojure10
c1710
sys10
micropython10
Programming languages (30)
Github contributions (5)
dhall-lang/dhall-lang
Dec 2018 - Oct 2021
Maintainable configuration files
Role in this project:
Backend Developer & Test Automation Engineer
Backend Developer & Test Automation EngineerContributions:1 release, 16 reviews, 81 commits in 2 years 10 months
Contributions summary:Philip primarily contributed to the Dhall language's testing infrastructure and core functionality. Their work focused on fixing and improving parser tests, including correcting type annotations and handling of various syntax elements. They also improved documentation for existing tests and added new unit tests for features such as import resolution, type inference, and binary decoding, while also refactoring test code. Furthermore, the user made changes to the test suite, including ensuring that tests use modern features and are well-organized.
configurationconfiguration-filesconfigdotfilesdhall
replicate/cog
Jan 2023 - Mar 2025
Containers for machine learning
Role in this project:Backend Developer
Backend DeveloperContributions:37 reviews, 39 PRs, 73 pushes in 2 years 1 month
Contributions summary:Philip primarily focused on improving the backend infrastructure and functionality of the `cog` project, which is a containerization tool for machine learning. Their commits addressed issues with OpenAPI schema generation, optimized stream handling, and fixed race conditions in the testing environment. The user also refactored the codebase to support newer Python versions and improved the worker's ability to handle concurrent predictions.
containerscudapytorchdeep-learningdocker
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.