Rick Chao
Summary
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RockstarRick Chao is a Principal Machine Learning Engineer and technical lead with 11+ years building scalable, fault-tolerant distributed training systems and ML platforms, currently based in Mountain View. He led Keras and TensorFlow distributed training at Google, architecting multi-worker/accelerator solutions and tooling that scaled to 256+ workers and thousands of steps per second, and now heads ML platform efforts at Snap. His open-source contributions to TensorFlow and Keras span core training features, early-stopping hooks, fault-tolerant evaluators, and documentation and testing infrastructure—work that improves usability for both researchers and production teams. Comfortable bridging deep engineering and clear technical writing, he combines production-grade backend engineering with a knack for making complex distributed workflows testable and reliable.
12 years of coding experience
Github Skills (12)
neural-network10
keras10
machine-learning10
deep-learning10
tensorflow10
early-stopping10
python10
documentation10
testing9
software-quality9
apidoc7
api7
Programming languages (6)
Github contributions (5)
tensorflow/estimator
Nov 2018 - Oct 2020
TensorFlow Estimator
Role in this project:
Back-end Developer
Back-end DeveloperContributions:22 commits, 10 comments, 1 issue in 1 year 11 months
Contributions summary:Rick's contributions center around enhancing the TensorFlow Estimator library by adding and exporting new functionalities, primarily related to early stopping mechanisms. They introduced features like `make_early_stopping_hook`, `stop_if_higher_hook`, `stop_if_lower_hook`, and `stop_if_no_increase_hook`, enabling users to control and optimize their training processes. Furthermore, the user integrated testing frameworks to validate the newly implemented features. This work improves the control and usability of TensorFlow Estimator.
tensorflow-estimator
keras-team/keras
Apr 2021 - Nov 2022
Deep Learning for humans
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:66 reviews, 75 commits, 7 PRs in 1 year 7 months
Contributions summary:Rick contributed to the Keras deep learning library by fixing error messages and improving code quality. They addressed issues in multiple files related to optimizers, datasets, and training, ensuring better usability and clarity. Furthermore, the user implemented changes related to the SidecarEvaluator, allowing for fault-tolerant training and more robust checkpoint management. These contributions enhanced the library's stability and functionality for machine learning model development.
deep-learningtensorflowneural-networksmachine-learningdata-science
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