Ethan Tang
Santa Clara, CA + Waterloo, ON, Canada
Summary
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RockstarEthan Tang is a Senior Software Engineer focused on AI/ML runtime and infrastructure with 10 years of experience, currently advancing Mosaic ML research at Databricks from California. He built production ML platforms at Nuro and NVIDIA for autonomous systems—optimizing reinforcement learning throughput, scaling NVAutonet, and accelerating inferencing and data pipelines. His open-source work on NVIDIA/DIGITS includes refactoring GoogLeNet and improving TensorFlow model handling and serving, demonstrating hands-on skill shipping deep learning tooling. A University of Waterloo computer engineering graduate, he pairs backend and systems chops (C#, test automation, backend web stacks) with deep learning expertise to turn research models into efficient, production-ready platforms.
11 years of coding experience
Github Skills (14)
tensorflow210
machine-learning10
deep-learning10
trainings10
tensorflow10
python10
modeling10
ml-deployment9
debug9
continuous-deployment9
caffe8
version-control8
caffe28
ci-cd7
Programming languages (6)
Github contributions (5)
NVIDIA/DIGITS
May 2017 - Aug 2017
Deep Learning GPU Training System
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 27 commits, 31 PRs in 3 months
Contributions summary:Ethan's contributions primarily involve modifying and improving existing deep learning models within the NVIDIA DIGITS framework. They refactored the GoogLeNet architecture, addressing issues and adding comments. Moreover, the user focused on correcting issues related to TensorFlow model handling, specifically regarding file uploads, downloads, and model serving functionalities. The user also addressed bugs, linting issues, and version updates within the DIGITS project.
deep-learninggputorchmachine-learningtraining
ethantang95/OrbisBot
Dec 2015 - Oct 2016
Contributions:99 commits, 6 PRs, 89 pushes in 10 months
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