Shun Lin
Staff Software Engineer at Google
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolShun Lin is a Staff Software Engineer at Google with a decade of experience building privacy-conscious AI and machine learning systems from research prototypes to production. Based in Sunnyvale, he has progressed through senior engineering roles at Google since 2019 and brings prior engineering and product leadership experience from consulting and internships at Amazon and HPE. He is pragmatic about safety and security trade-offs in ML, contributing not only code but clearer user-facing docs and tooling—evident in meaningful TensorFlow Addons contributions such as Keras TQDM integration, TimeStopping tutorials, and bug fixes that improve training ergonomics. Collected academic grounding from UC Berkeley EECS underpins a pattern of shipping reliable, usable ML infrastructure while mentoring peers on privacy-aware engineering choices.
10 years of coding experience
8 years of employment as a software developer
Bachelor’s Degree Electrical Engineering and Computer Science, Bachelor’s Degree Electrical Engineering and Computer Science at University of California, Berkeley
English, Mandarin, Chinese
Stackoverflow
11reputation
907reached
1answer
0questions
Github Skills (6)
callback10
keras10
machine-learning10
tensorflow10
python10
documentation10
Programming languages (6)
Github contributions (5)
tensorflow/addons
Oct 2019 - Apr 2020
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
Role in this project:
Technical Writer & ML Engineer
Technical Writer & ML EngineerContributions:10 commits, 18 PRs, 3 pushes in 5 months
Contributions summary:Shun significantly contributed to the project by adding and improving documentation. They introduced a TQDM progress bar tutorial, fixed typos in existing tutorials, and provided a tutorial for TimeStopping callbacks. Furthermore, the user added get_config to the TQDM Progress Bar for Keras, and addressed bugs when using fit generator, showing their involvement in code maintenance. This indicates an active role in improving the usability and explainability of the TensorFlow Addons library, specifically around the integration of machine learning and training progress.
python2-xdeep-learningaddonssig
DiversaTech/diversatech.github.io
Dec 2016 - Dec 2018
The website for DiversaTech at UC Berkeley
Contributions:266 commits, 280 pushes in 2 years
berkeleyjekylluc-berkeley
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