Huan-ping Su is a Backend Distributed Systems Engineer based in Taipei with eight years of experience building and operating large-scale, cloud-native data and ML infrastructure. He combines academic research in distributed systems and ML platforms with hands-on engineering at Union.ai and contributions to flagship Apache projects like Hadoop, Spark, and HBase. An active open-source maintainer and Apache Submarine PMC member, he has improved core functionality, type-safety, and deployment robustness across ecosystems including Flyte, Kubeflow, and Ray on Kubernetes. His work spans backend development, DevOps, and documentation—bringing changes that range from scheduler optimizations and typing improvements in PySpark to Kubernetes operator fixes and SDK enhancements in FlyteKit. Comfortable moving between low-level refactors and user-facing experience improvements, he often focuses on reliability and reproducibility for ML workflows. Outside of code, he blends research rigor with practical engineering—having co-authored work on Apache Submarine while contributing production fixes to widely used open-source platforms.
8 years of coding experience
1 year of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at National Cheng Kung University
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at National Dong Hwa University
Submarine is Cloud Native Machine Learning Platform.
Role in this project:
Back-end & DevOps Engineer
Contributions:468 reviews, 102 commits, 121 PRs in 2 years 11 months
Contributions summary:Huan-ping's commits primarily focused on back-end development and infrastructure updates within the Apache Submarine project. They updated the Spark version, added a submarine-sdk module, and enhanced the build process. Additionally, the user addressed issues and made changes to Docker-related configurations, including updating images and fixing build errors. The user's contributions impacted the project's codebase and its supporting infrastructure.
Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.
Role in this project:
Backend Developer
Contributions:44 releases, 1944 reviews, 964 commits in 4 years 5 months
Contributions summary:Huan-ping primarily focused on enhancing the FlyteKit SDK, which is used for developing Flyte tasks and workflows in Python. Their contributions included adding support for typing.Tuple for multiple return values, which required code modifications in core modules and plugins. These changes demonstrate a focus on improving type safety and code quality within the FlyteKit library and extending its functionality. Furthermore, the commits reflect an understanding of the Flyte ecosystem.
flytepythondataflyte-taskspypi
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Huan-ping Su - Backend Distributed Systems Engineer at Union.ai