Xu Zou
Senior Software Engineer at Moveworks
Beijing, United States
Summary
👤
Senior🎓
Top SchoolXu Zou is a senior software engineer with 8 years of experience building backend systems in Java, Scala, and Go, currently driving production efforts at Moveworks after roles at TikTok and Rally Health. He holds an M.S. in Computer Engineering from Northeastern and began his career with hands-on internships in China and the U.S., blending strong academic foundations with pragmatic product delivery. Xu has notable open-source contributions to OneFlow, improving memory management and performance in a scalable deep learning framework—a hint of systems-level expertise beyond typical web backends. Comfortable across web and low-level performance work, he focuses on reliable, efficient software and has a track record of simplifying complex codepaths to boost runtime efficiency.
7 years of coding experience
7 years of employment as a software developer
Master of Science (M.S.) Computer Engineering, Master of Science (M.S.) Computer Engineering at Northeastern UniversityBachelor of Engineering (B.E.) Automation, Bachelor of Engineering (B.E.) Automation at Beijing Institute of Technology
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (12)
neural-network10
memory-management10
machine-learning10
c-language10
deep-learning10
cprogramming-language10
data-structure9
algorithm9
data-structures9
algorithms9
distributed-systems8
cuda8
Programming languages (1)
Github contributions (3)
Oneflow-Inc/oneflow
Jun 2018 - Aug 2018
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:32 commits in 2 months
Contributions summary:Xu primarily focused on memory management and optimization within the OneFlow deep learning framework. Their contributions involved allocating memory for shared memory IDs, simplifying code, and implementing functionalities like sharding and unsharing registers. Furthermore, they addressed bugs related to memory allocation and register management, improving the framework's efficiency. The user also made changes related to Eigen library and the Chain Act Graph, related to performance improvements and II calculations.
caffe2tensorflowframework-learningchainerdeep-learning-framework
Avnu/gptp
Apr 2019 - May 2019
Contributions:2 comments, 1 issue in 1 month
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