Wang Zhang
Software Engineer at ByteDance
San Jose, California, United States
Summary
👤
Senior🎓
Top SchoolWang Zhang is a software engineer with 11 years of experience specializing in cloud-native AI/ML infrastructure and distributed training systems, currently contributing to ByteDance from San Jose. He has driven elastic and fault-tolerant training features across Kubeflow/training-operator and co-authored projects like Kube-Queue and FTLib that optimize GPU sharing, job scheduling, and resilience for large-scale ML workloads. At Tencent and Caicloud he built multi-cluster RL schedulers and GPU-sharing solutions that reclaim fragmented and spot resources for actors and learners, demonstrating practical expertise in resource elasticity and scheduling plugins. An approver on Kubeflow’s training-operator and author of FTLib, he combines academic rigor from Carnegie Mellon with hands-on systems engineering to bridge low-level GPU techniques and higher-level orchestration. Notably, he helped design veRL’s single-controller architecture and has a track record of enabling elastic training across TensorFlow, PyTorch, Horovod and more.
11 years of coding experience
7 years of employment as a software developer
Master's degree, Mechanical Engineering, Master's degree, Mechanical Engineering at 美国卡内基梅隆大学Bachelor's degree, Mechanical Engineering, Bachelor's degree, Mechanical Engineering at 浙江大学
Github Skills (45)
agentic10
java10
connection-pool10
high-performance10
mysql9
jdbc9
sql9
ai9
scale9
go9
database9
serverless9
stream9
cloud-native8
agent8
Programming languages (4)
Github contributions (5)
jaxsoy/jaxsoy.github.io
Jul 2016 - Feb 2017
Contributions:30 commits, 62 pushes, 1 branch in 7 months
iamjohnnyzhuang/Azkaban-HA-Bootstrap
Nov 2018 - Nov 2019
A solution for azkaban web service HA
Contributions:4 commits, 2 PRs, 3 pushes in 11 months
azkabanwebservice
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