Jingxin Ye
Member Of Technical Staff at Stealth AI Startup
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolJingxin Ye is a Member of Technical Staff based in the San Francisco Bay Area with 11 years of experience building production-scale ML and cloud infrastructure. He has delivered deep learning and large-scale data systems across Google and Facebook, from extracting information from Street View imagery to graph neural recommendation systems and Cloud TPU/GPU platform work. At Google he improved TPU tooling and automation—contributing to the widely used tensorflow/tpu repo by adding preemptible TPU support and fixing TPU orchestration bugs—demonstrating a blend of low-level systems, DevOps, and ML engineering. With a PhD in Computational Science from UC San Diego and earlier research in Bayesian inference and numerical optimization, he brings strong mathematical rigor to RL infrastructure and model deployment. Now at a stealth AI startup, he focuses on reinforcement-learning infrastructure, applying production-hardened cloud expertise to accelerate experimental ML workflows.
12 years of coding experience
14 years of employment as a software developer
University of California, San DiegoBachelor's Degree, Applied Physics, Bachelor's Degree, Applied Physics at University of Science and Technology of China
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (10)
ray10
cloud-infrastructure10
python10
tpu10
gcp10
kubernetes-pods9
devops9
kubernetes9
automations8
automation8
Programming languages (5)
Github contributions (5)
tensorflow/tpu
Mar 2023 - Sep 2023
Reference models and tools for Cloud TPUs.
Role in this project:
DevOps & Cloud Engineer
DevOps & Cloud EngineerContributions:3 reviews, 20 PRs, 15 pushes in 6 months
Contributions summary:Jingxin primarily focused on enhancing the tools and infrastructure for running and managing TPUs. They introduced the functionality to create preemptible TPUs and modified existing scripts to include this option. Furthermore, they corrected a bug related to updating the Ray TPU IP address. The contributions included modifications to core components like `tpu_api.py`, `tpu_controller.py`, and configuration scripts, streamlining the deployment and management process of TPUs in the cloud environment.
cloud
yejingxin/yejingxin.github.io
May 2019 - Sep 2022
Contributions:10 pushes, 1 branch in 3 years 5 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.