Hang Wu is a senior machine learning engineer with 9 years of experience specializing in big data pipelines, ETL, and scalable data systems. Based in Virginia and holding an M.S. in Data Science from The George Washington University, he has built high-performance ingestion and computation stacks using Kafka, Cassandra, Spark, Pig, and Hive. At ByteDance he applies ML engineering rigor to large-scale data problems, and his open-source contributions to Alluxio demonstrate hands-on backend work fixing shell command path handling and improving copy semantics. He is actively seeking data engineering or software engineering roles where he can design or improve big data frameworks and pipelines. Beyond typical tooling, he brings proven experience tightening filesystem behavior in distributed data orchestration—an often overlooked but critical reliability touchpoint. Reachable at wuhang0613@gmail.com.
9 years of coding experience
Master’s Degree, Data Science, Master’s Degree, Data Science at The George Washington University
B.S, Traffic Engineering, B.S, Traffic Engineering at Harbin Institute of Technology
Alluxio, data orchestration for analytics and machine learning in the cloud
Role in this project:
Back-end Developer
Contributions:22 commits, 9 PRs, 48 comments in 1 month
Contributions summary:Hang primarily contributed to the Alluxio project by fixing issues related to the copy commands and improving their functionality. Their commits show a focus on correcting path handling in copy operations, ensuring correct behavior with relative and absolute paths. Additionally, they modified test cases, suggesting an active role in maintaining and improving the shell commands.
Contributions:126 commits, 124 pushes, 1 branch in 15 days
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Hang Wu - Sr Machine Learning Engineer at ByteDance