Kyle Kosic is a builder and full-stack site reliability engineer with nine years of experience designing scalable, automated distributed systems for AI and HPC. He has driven infrastructure and reliability work at OpenAI and co-founded xAI to lead infrastructure during early product development, and now builds at a stealth startup in San Francisco. With a strong foundation in mathematics and machine learning (MS CS, Georgia Tech; BS in Theoretical and Mathematical Physics), he blends rigorous quantitative thinking with practical engineering. An active open-source contributor, Kyle improved Rust bindings for TensorFlow—fixing memory issues and adding op-list parsing—to make core ML tooling more robust. He favors systems-level work in Rust and has a track record of shipping production-grade, performance-sensitive components across startups and research-driven organizations.
8 years of coding experience
10 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of Technology
Bachelor of Science (BS), Theoretical and Mathematical Physics, Applied Mathematics, Bachelor of Science (BS), Theoretical and Mathematical Physics, Applied Mathematics at The University of Alabama in Huntsville
Contributions:20 commits, 3 PRs, 15 comments in 1 month
Contributions summary:Kyle primarily focused on implementing and refining the Rust bindings for TensorFlow. Their work involved adding functionality like `TF_GetOpList` to load and parse operation definitions from TensorFlow libraries. They addressed issues with memory allocation and dereferencing, improving the stability of the bindings. The contributions also included refactoring and correcting errors, making the library's core functionality more robust.
Configs, scripts, instructions for my development environments.
Contributions:6 PRs, 151 pushes, 11 branches in 2 years 5 months
gitpodazerothcoreinstructionsconfigsconfig
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