Tao Wang
Hangzhou City, Zhejiang, China
Summary
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RockstarTao Wang is a seasoned software engineer with 12 years of experience and a strong academic foundation (M.S. in Computer Science) who blends backend systems engineering with test automation and DevOps. He has contributed to high-profile open-source projects such as Ray, Apache Flink, Alluxio, and Apache Spark—improving testing infrastructure, streaming and deployment robustness, and production stability. Previously a senior engineer at Visa and now at LinkedIn, he brings practical experience in large-scale distributed systems, performance tuning, and security configuration. Tao’s background spans IoT, computer vision, and operations research—where his intern work produced real cost savings via optimization—highlighting a rare mix of algorithmic rigor and hands-on engineering. Colleagues would point to his meticulous, test-first approach and his wry GitHub motto, “I don't produce bugs. I think,” as emblematic of his confidence and attention to quality.
12 years of coding experience
Github Skills (31)
debugging10
debug10
spark10
apache-flink10
big-data10
flink-sql10
tachyons10
java10
scala10
javas10
performance-optimization10
yarn310
yarnpkg10
yarn-berry10
yarn210
Programming languages (7)
Github contributions (5)
ray-project/ray
May 2020 - Aug 2022
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:
Test Automation Engineer & DevOps Engineer
Test Automation Engineer & DevOps EngineerContributions:279 reviews, 126 commits, 163 PRs in 2 years 3 months
Contributions summary:Tao's commits focused on enhancing the test suite and improving the testing infrastructure of the Ray project. The user made changes to the core worker test setup, integrating test managers to consolidate and prevent code duplication. The user also made changes to test files and build configurations by modifying the relevant arguments and dependencies. In addition, the user made contributions to the test setup utility, adding functionality to start, stop, and flush redis servers, in order to test related components.
pythonconsistsruntimetensorflowserving
apache/spark
Dec 2014 - Jul 2015
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 commits, 50 PRs, 263 comments in 7 months
Contributions summary:Tao primarily focused on code cleanup and optimization within the Apache Spark codebase, deleting unused variables and handling unused assignments to improve code readability and efficiency. They also addressed several minor issues, including fixing typos, modifying configurations, and improving the structure of the web UI. Furthermore, the user implemented changes to enhance the performance of the load-balancing of concurrently-submitted drivers.
analyticspythondata-processingsqlapache
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