Chris Blust
Embedded Software Engineer at Zipline
San Francisco, California, United States
Summary
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Rockstar🎓
Top SchoolChris Blust is an embedded firmware engineer with 11 years of experience building real-time systems and vehicle integrations, currently contributing to Zipline in San Francisco. He has led firmware and SIL efforts at Aptera and RIT Racing, designing layered architectures, CAN/LIN simulations, and CI-driven test frameworks that bridge hardware and software. His background spans battery management, chassis and powertrain firmware at Tesla, and hands-on FPGA and hardware-in-the-loop work, showing a strong mix of low-level C/FreeRTOS and higher-level Python tooling. An active contributor to Unity-Technologies/ml-agents, he’s extended sensor support and flexible action spaces, reflecting a practical interest in ML-enabled simulations. Colleagues know him for turning complex embedded requirements into repeatable, testable systems and for building developer-friendly tooling that accelerates integration.
11 years of coding experience
2 years of employment as a software developer
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Rochester Institute of Technology
Stackoverflow
3,944reputation
401kreached
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3questions
math
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Github Skills (25)
machine-learning10
reinforcement-learning10
tensorflow10
sensor10
unity3d10
geometry9
algorithm9
matrix9
ml9
aiml9
math9
csharp9
dotnet-core9
ai9
optimization9
Programming languages (9)
Github contributions (5)
Unity-Technologies/ml-agents
Jun 2019 - Jun 2021
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Role in this project:
ML Engineer
ML EngineerContributions:9 releases, 1008 reviews, 879 commits in 2 years
Contributions summary:Chris primarily focused on improving the ML-Agents toolkit. The commits involve refactoring and adding new sensors, notably incorporating the Ray Perception Sensor and extending the support for diverse observation types. The changes also include the addition of utilities for working with Unity and the integration of more flexible action spaces to the training process, demonstrating expertise in enhancing the core functionality of the toolkit.
servedeep-reinforcement-learningtrainingunityreinforcement
lyft/gunicorn
Sep 2016 - Jan 2023
gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications.
Contributions:2 PRs, 1 branch, 1 comment in 6 years 5 months
unixweb-servergunicornunicornhttpd
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