Anthony Hsu
Staff Software Engineer at Google
Sunnyvale, California, United States
Summary
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Rockstar🎓
Top SchoolAnthony Hsu is a Staff Software Engineer in Sunnyvale with 12 years of experience building and optimizing large-scale distributed systems, currently working on AlloyDB at Google. He has deep hands-on expertise in storage and replication for Postgres-compatible systems, and a strong background in Hadoop/YARN and workflow orchestration from his leadership on TonY and extensive Azkaban contributions. At LinkedIn he shipped infrastructure for distributed ML (Horovod, history server) and led data format and compliance efforts that materially reduced storage and compute costs. His work spans backend, DevOps, and performance tuning—often surfacing in open-source fixes that improve job runners, log parsing, and deployment reliability. Anthony holds an M.S. from Carnegie Mellon and a B.S. from Yale, blending rigorous academic training with a practical knack for productionizing complex data and ML workflows.
12 years of coding experience
10 years of employment as a software developer
B.S. cum laude with distinction in major Computer Science, B.S. cum laude with distinction in major Computer Science at Yale UniversityM.S. Computer Science, M.S. Computer Science at Carnegie Mellon University
Stackoverflow
3,447reputation
471kreached
16answers
11questions
Github Skills (26)
back-end-development10
apache-pig10
workflow-engine10
hadoop10
java10
javas10
hive10
tensorflow10
sql10
azkaban10
teradata9
build-automation9
python8
cicd8
javascript8
Programming languages (8)
Github contributions (5)
tony-framework/TonY
Sep 2018 - Jul 2019
TonY is a framework to natively run deep learning frameworks on Apache Hadoop.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:12 releases, 77 commits, 174 PRs in 9 months
Contributions summary:Anthony primarily focused on improving the build process and infrastructure of the TonY framework. Their contributions include running Play tests during the build, removing and refactoring registration timeout and retry logic, and injecting Azkaban metadata and TonY version into the configuration. They also addressed issues related to TensorBoard port management and other deployment aspects. Additionally, the user worked on resolving issues related to the distributed MNIST TensorFlow example and the TonY Portal.
horovoddeep-learningmachine-learningapachehadoop-yarn
azkaban/azkaban-plugins
Oct 2013 - Apr 2015
Plugins for Azkaban.
Role in this project:Back-end Developer
Back-end DeveloperContributions:146 commits, 16 PRs, 7 pushes in 1 year 6 months
Contributions summary:Anthony primarily contributed to the Reportal plugins, focusing on enhancing and refining the Azkaban plugin ecosystem. They made improvements to the ReportalPigRunner, HiveRunner, and TeradataRunner job types. The user also implemented new features related to report email notifications, and adding functionality to the Reportal edit page.
jenkins-api-pluginpluginazkabanpluginsjava
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