Wenzhe Li
Staff Software Engineer Tech Lead Manager at Google
San Francisco Bay Area United States
Summary
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Rockstar🎓
Top SchoolWenzhe Li is a Staff Software Engineer and Tech Lead Manager at Google with 12 years of experience building large-scale cloud, distributed systems, and ML infrastructure. He leads work on Vertex AI training, hyperparameter tuning, and Vizier, driving production-ready ML training and deployment capabilities used across Google Cloud. Proficient in Java and C/C++, he has a strong background in big data processing and previously contributed to Payments Data Warehouse and high-performance systems at AWS (Redshift). His open-source contributions to GoogleCloudPlatform/cloudml-samples show hands-on ML engineering with TensorFlow, model training pipelines, and cloud export workflows. Based in the San Francisco Bay Area, he blends research-rooted rigor from Carnegie Mellon with practical product impact at Google. Colleagues know him for turning complex training infrastructure problems into reliable, scalable services that accelerate ML adoption.
12 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering (B.E.), Computer Science, 3.65, Bachelor of Engineering (B.E.), Computer Science, 3.65 at Nankai UniversityMaster of Science (M.S.), Information Networking, 3.50, Master of Science (M.S.), Information Networking, 3.50 at Carnegie Mellon University
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (7)
machine-learning10
tensorflow10
python10
keras9
gcp8
sample-data7
android-sample7
Programming languages (4)
Github contributions (5)
GoogleCloudPlatform/cloudml-samples
Jan 2017 - Feb 2019
Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples
Role in this project:
ML Engineer
ML EngineerContributions:40 commits, 11 PRs, 18 pushes in 2 years 1 month
Contributions summary:Wenzhe contributed to several machine learning projects within the repository, primarily focusing on TensorFlow. The commits show modifications to training scripts, model definitions, and evaluation pipelines for various models, including MNIST, flowers, and ResNet. The user also appears to be working with hyperparameter tuning and model exporting to Google Cloud Storage. These changes indicate a focus on model training and deployment.
gcpcloudml-samplescloudmldeep-learninggooglecloudplatform
GoogleCloudPlatform/cloudml-hypertune
May 2018 - Dec 2019
Contributions:9 commits, 1 PR, 7 pushes in 1 year 6 months
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