Yunzhi Zhang
Member Of Technical Staff at xAI
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolYunzhi Zhang is a software engineer with eight years of experience building distributed systems and ML infrastructure, currently a Member of Technical Staff at xAI in Palo Alto. He combines a PhD pursuit at Stanford with hands-on engineering roles across Bay Area AI teams, including a research stint at Google DeepMind and engineering work at Anyscale and Covariant. Yunzhi has contributed to the high-profile Ray project, extending its dashboard and backend in Python and C++ to surface resource, actor, and worker metrics for production-scale ML workloads. His background in pure mathematics and CS from UC Berkeley informs a methodical approach to performance-sensitive telemetry and debugging in distributed runtimes. He has bridged research and production before—working on RL/robotics at Berkeley AI Research and teaching algorithmic courses—so he’s comfortable moving ideas from papers into reliable systems. Colleagues would describe him as an engineer who blends rigorous theory with pragmatic backend implementation to make complex systems observable and actionable.
8 years of coding experience
1 year of employment as a software developer
Bachelor of Arts - BA, Pure Mathematics and Computer Science, Bachelor of Arts - BA, Pure Mathematics and Computer Science at University of California, BerkeleyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Stanford University
Github Skills (12)
ray10
distributed-systems10
dashboard10
back-end-development10
python10
cprogramming-language9
c-language9
data-visualization8
data-visualisation8
machine-learning8
data-visualizations8
llm8
Programming languages (4)
Github contributions (5)
ray-project/ray
Dec 2019 - Jan 2020
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:11 commits, 12 PRs, 4 comments in 1 month
Contributions summary:Yunzhi primarily contributed to the Ray dashboard, implementing features and addressing issues related to resource display, actor status, and worker statistics. Their work involved modifying backend code in Python and C++ to collect and expose information about node resources, task execution, and actor states within the dashboard. The contributions also involved integrating worker statistics within the dashboard, providing insights into performance metrics, and extending the web UI.
pythonconsistsruntimetensorflowserving
iclavera/meta-mb
Jun 2019 - Dec 2019
Contributions:316 commits in 6 months
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