Gal Oshri
Senior Staff Product Manager at Databricks
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolGal Oshri is a Senior Staff Product Manager in San Francisco with 12 years building developer-first ML and AI platform products across Databricks, AWS SageMaker, Google’s TensorFlow, and Microsoft. He has led flagship efforts like TensorBoard and TensorBoard.dev—contributing technical documentation to TensorFlow’s visualization toolkit—and drove SageMaker Model Training to scale for enterprise customers. Known for turning research tools into production-grade developer experiences, he shipped profiling and experiment management features that delivered sizable speedups and reproducibility for ML teams. His background spans product leadership, program management, and open-source collaboration, and he pairs Princeton CS rigor with a knack for clear technical writing that improves adoption and developer workflows.
12 years of coding experience
11 years of employment as a software developer
International Baccalaureate, International Baccalaureate at United World College of South East AsiaA.B. Computer Science, A.B. Computer Science at Princeton University
Stackoverflow
396reputation
19kreached
12answers
0questions
Github Skills (12)
markdown10
tensorboard10
markdown-it10
documentation10
tensorflow9
hyperparameter-tuning8
collections6
deep-learning6
machine-learning6
artificial-intelligence6
mlnet6
python6
Programming languages (9)
Github contributions (5)
tensorflow/tensorboard
Feb 2019 - Mar 2020
TensorFlow's Visualization Toolkit
Role in this project:
Technical Writer
Technical WriterContributions:4 reviews, 8 commits, 21 PRs in 1 year 1 month
Contributions summary:Gal primarily contributed to documentation, creating and updating tutorials and guides within the TensorFlow/TensorBoard repository. Their work included adding quickstart guides, tutorials on hyperparameter tuning, and tutorials on using TensorBoard within notebooks and on TensorBoard.dev. The contributions involved writing and formatting documentation, fixing broken links, and addressing feedback to improve the clarity and usability of the tutorials.
machine-learningtensorflowvisualization
p-stav/goOut
Dec 2013 - Jul 2015
Contributions:138 commits, 28 pushes in 1 year 6 months
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