Binyao Jiang
Member Of Technical Staff at xAI
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolBinyao Jiang is a systems software engineer with a decade of experience building reliable, high-performance infrastructure and ML inference optimizations across top-tier tech companies. Currently a Member of Technical Staff at xAI, he delivered 10–20% end-to-end speedups for Grok Imagine and enabled AMD GPU (ROCm) support for LLM inference. His LinkedIn tenure progressed from intern to staff engineer, and he has production experience at Microsoft and contributions to the well-known Azkaban workflow manager where he improved Kubernetes containerization, thread safety, flow retry reliability, and Hadoop config handling. Comfortable spanning backend, DevOps, and ML deployment, he combines research-informed rigor from UIUC with hands-on open-source impact. Based in Sunnyvale, he brings a practical focus on robustness and performance when moving complex systems into production.
9 years of coding experience
7 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of Illinois Urbana-ChampaignBachelor's degree Computer Science, Bachelor's degree Computer Science at Shanghai Jiao Tong University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
javas10
kubernetes10
workflow-engine10
back-end-development10
containerization10
java10
kubernetes-pods10
concurrency9
devops9
scheduling9
hadoop8
Programming languages (4)
Github contributions (5)
azkaban/azkaban
Mar 2022 - Nov 2022
Azkaban workflow manager.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:206 reviews, 45 commits, 122 PRs in 9 months
Contributions summary:Binyao primarily focused on improving the Azkaban workflow manager, particularly in containerized environments. They implemented thread safety within Kubernetes containerized implementations, making changes to the KubernetesContainerizedImpl. Additionally, the user worked on enhancing the reliability of the system by addressing issues with flow retries and by ensuring that flow logs are properly handled when containers are unavailable. They also made infrastructure-related changes, such as adding a local path for adding Hadoop configurations.
workflow-engineschedulingazkabanworkflow
byjiang1996/azkaban
Feb 2022 - Aug 2023
Azkaban workflow manager.
Contributions:2 PRs, 129 pushes, 60 branches in 1 year 5 months
iftttazkabanworkflow
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