Byron Hsu
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolByron Hsu is a Member of Technical Staff and ML systems engineer with nine years of experience building large-scale GPU clusters, high-performance GPU runtimes, and end-to-end ML platform tooling. He has led inference and pretraining infrastructure at xAI and drove LLM training and distributed optimization efforts at LinkedIn, contributing to DeepSpeed ZeRO++ and authoring the fast-growing Liger-Kernel project. Byron is an active open-source committer across Flyte, Apache, and SGLang, where he optimized Triton-based attention kernels and helped productionize serving frameworks for large language and vision models. Based in Palo Alto, he blends low-level kernel work with cloud-native orchestration—scaling Kubernetes to thousands of GPUs and designing disaggregated serving and RDMA services. Notably, he bridges research and production: his work underpins ICML-accepted optimizations and powers 100B+ scale pretraining pipelines. He holds an MEng in Computer Science from UC Berkeley and maintains a visible community presence via GitHub and X.
9 years of coding experience
4 years of employment as a software developer
Master of Engineering - MEng Computer Science, Master of Engineering - MEng Computer Science at University of California, BerkeleyBachelor of Science - BS Electrical and Electronics Engineering, Bachelor of Science - BS Electrical and Electronics Engineering at National Taiwan University
Github Skills (29)
pytorch10
javascript10
apidoc10
typescript10
triton10
api10
typescript-types10
cuda10
typescripts10
angular10
mlflow9
python9
inference9
transformer9
docker8
Programming languages (14)
Github contributions (5)
apache/submarine
Oct 2020 - Jul 2021
Submarine is Cloud Native Machine Learning Platform.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:48 reviews, 37 commits, 47 PRs in 9 months
Contributions summary:Byron primarily focused on enhancing and maintaining the front-end web interface and backend functionality of the Submarine project. Their contributions included fixing bugs, such as clarifying error messages, refactoring code for improved maintainability, and implementing new features like the tensorboard integration and model serving API. They also improved the codebase through refactoring, which involved splitting complex components into smaller ones and using Angular's built-in authguard. Furthermore, the user provided documentation and improved existing documentation for users and developers.
machine-learning-platformlearning-platformdeep-learningnotebookdocker
sgl-project/sglang
Aug 2024 - Mar 2025
SGLang is a fast serving framework for large language models and vision language models.
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:98 reviews, 160 PRs, 213 pushes in 7 months
Contributions summary:Byron contributed to the SGLang project by focusing on optimizing and extending the Triton-based attention kernels. Their work included removing unnecessary initializations, supporting non-power-of-two head dimensions in extend and decode attention, and improving the overall performance of the attention mechanisms. The user also made code changes to support the use of various model architectures in SGLang, which shows that they are actively working on the project's core functionalities.
cudadeepseekdeepseek-llmdeepseek-r1deepseek-r1-zero
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