Shuo Ouyang is a deep learning framework engineer with nine years of experience building high-performance machine learning systems, currently at TuSimple in Beijing. He has strong expertise with MXNet, TensorFlow and distributed training tooling like Horovod, and is an active contributor to the MXNet project. Prior roles include developing ML engine components at Meituan, reflecting experience shipping production-grade infrastructure in fast-paced companies. He holds a master's from the National University of Defense Technology and a bachelor’s from Central South University, grounding his work in solid academic training. Based in Chaoyang District and open to opportunities, he combines low-level performance tuning with practical deployment know-how. An interesting signal: beyond corporate work he publicly signals recruitability and networking intent on GitHub, indicating readiness to engage with new teams.
Contributions:19 commits, 79 pushes, 2 branches in 1 year
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