Zhitao Li
Member Of Technical Staff at Microsoft AI
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolZhitao Li is a Director of Engineering based in Palo Alto with 11 years of experience building and leading large-scale AI and infrastructure teams, currently heading Uber’s AI infrastructure org. He has deep distributed-systems and DevOps roots from early contributions to prominent open-source projects like Apache Mesos and Aurora, where he improved scheduler/executor reliability and service discovery. Zhitao’s career spans senior technical leadership roles at Google (including work on TensorFlow Extended) and multiple tenures at Uber, reflecting both hands-on engineering and management at hyperscale. He combines a rigorous testing and systems mindset—evident from extensive executor lifecycle and master API work—with product-focused delivery, enabling ML platforms to move from prototype to production. Trained with an M.S. in Computer Science from Stony Brook and a B.S. from Zhejiang University, he’s comfortable shifting between low-level infrastructure code and high-level AI platform strategy.
11 years of coding experience
18 years of employment as a software developer
B.S Computer Science, B.S Computer Science at Zhejiang UniversityM.S Computer Science, M.S Computer Science at Stony Brook University
Stackoverflow
1reputation
0reached
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Github Skills (17)
mesos10
c-language10
back-end-development10
testing10
java10
aurora10
javas10
cprogramming-language10
dockers9
cicd9
docker9
build-automation9
python8
junit8
jtest8
Programming languages (8)
Github contributions (5)
apache/mesos
Jul 2016 - Jun 2019
Apache Mesos
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:87 commits, 5 PRs, 3 comments in 2 years 11 months
Contributions summary:Zhitao's contributions centered on enhancing the core functionality of the Apache Mesos project, specifically related to executor management and container lifecycle events. They implemented features to notify framework schedulers of executor exits, ensuring more reliable event handling and improved system stability. Furthermore, the user's code changes show a focus on testing, with extensive modifications to the test suite, including adding tests for edge cases related to the executor's lifecycle. The contributions also show work on the master API.
mesoscpluspluscloud
apache/aurora
Jan 2016 - Sep 2016
Apache Aurora - A Mesos framework for long-running services, cron jobs, and ad-hoc jobs
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:6 commits in 7 months
Contributions summary:Zhitao contributed to the Apache Aurora scheduler, focusing on core functionalities and infrastructure. Their work included enhancements to resource allocation, specifically accepting resource offers from multiple framework roles. They also addressed build and deployment processes by adding dependencies like `jq` to the build process. Furthermore, the user implemented features to set `DiscoveryInfo` in Mesos tasks, enabling alternative service discovery methods.
cronmesosaurora
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