Jiaying Zhang
Technical Lead Manager at Google
Saratoga, California, United States
Summary
👤
Senior🎓
Top SchoolJiaying Zhang is a seasoned technical lead manager with 26 years of experience building and scaling cloud-native and infrastructure systems, currently driving Anthos on VMware at Google from Saratoga, CA. She blends hands-on engineering—authoring Kubernetes device plugins for GPU support and leading GKE Managed Node/GKE Autopilot work—with people leadership, hiring and aligning cross-team efforts to deliver strategic product goals. Her deep systems pedigree spans Linux kernel tracing and Ext4 improvements to SDN routing and production storage projects, reflecting a rare combination of kernel-level expertise and cloud orchestration. Jiaying is an active contributor to open-source tooling for Kubernetes and test automation, having implemented core device plugin APIs and extended LTTng-based tracing for resilient automated testing. Known for stepping into on-call and customer-facing roles, she translates operational feedback into robust platform features. She holds a PhD in Computer Science from the University of Michigan and a B.S. from Tsinghua, underscoring a strong research-to-production trajectory.
26 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of MichiganB.S., Computer Science, B.S., Computer Science at Tsinghua University
Github Skills (15)
gcp10
kubernetes10
nvidia10
linux10
cloud-infrastructure10
go10
gpu10
python10
kubernetes-pods10
testing10
dockers9
docker9
automations8
automation8
bash4
Programming languages (6)
Github contributions (5)
GoogleCloudPlatform/container-engine-accelerators
Aug 2017 - Sep 2019
Collection of tools and examples for managing Accelerated workloads in Kubernetes Engine
Role in this project:
Cloud Engineer & DevOps Engineer
Cloud Engineer & DevOps EngineerContributions:26 commits, 24 PRs, 11 pushes in 2 years 1 month
Contributions summary:Jiaying primarily contributed to the development of a device plugin for NVIDIA GPUs, which involved setting up the environment, discovering GPU devices, and integrating with Kubernetes. They implemented the device plugin API, including ListAndWatch and Allocate functionalities. Key changes include supporting multiple API versions (v1beta1) and incorporating environment variables for CUDA-enabled containers.
workloadsgpuacceleratedkuberneteskubernetes-engine
autotest/autotest
Aug 2008 - Oct 2008
Autotest - Fully automated tests on Linux
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:5 commits in 1 month
Contributions summary:Jiaying significantly contributed to the testing framework by extending the Linux Tracing Toolkit (lttng) profiler. Their work involved enabling specific trace points, adding features like output file size limits and compression, and ensuring proper data flushing before system reboot. The user also addressed setup and initialization to ensure the framework is well-integrated with the existing test environment. This indicates a focus on automated testing and improving the overall testing process within the repository.
pythontest-automationtestinglinuxautomated-tests
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