Huaiwei Sun
Product Designer at Decagon
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolHuaiwei Sun is a product designer with 11 years of experience crafting simple, enjoyable user experiences for AI and developer-focused products. Based in Sunnyvale, she has led design for Vertex AI notebooks at Google and revamped Anyscale's platform UI, observability dashboards, and developer workflows, often stepping into PM, tech writing, and devRel roles to drive outcomes. As the founding product designer at Decagon, she applies a pragmatic, end-to-end approach from research and design systems to shipped implementations. Her background in HCI (Georgia Tech) and industrial design gives her a strong blend of user research rigor and visual/interaction craft. She also contributes to open-source observability docs for Ray—bridging backend/devops concerns with clearer developer-facing documentation. Colleagues describe her work mantra as making complex ML tooling feel simple and even fun.
11 years of coding experience
4 years of employment as a software developer
Master's degree, Human-computer Interaction, Master's degree, Human-computer Interaction at Georgia Institute of TechnologySummer semester exchange, 4.0/4.0, Summer semester exchange, 4.0/4.0 at Yale UniversityIndustrial Design, Industrial Design at Shanghai Jiao Tong University
English, Chinese
Github Skills (6)
ray10
python10
documentation10
debug9
debugging9
devops8
Programming languages (5)
Github contributions (5)
ray-project/ray
Aug 2021 - Dec 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:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:211 reviews, 7 commits, 43 PRs in 1 year 4 months
Contributions summary:Huaiwei primarily contributed to documentation and improvements related to the Ray project's observability features. Their work involved refining documentation structure, adding troubleshooting information for Ray client, and correcting installation instructions for Ray Tune within the documentation. The user also fixed warnings in the documentation and updated links related to Anyscale. Additionally, the user made contributions to improve code style and fix typos.
pythonconsistsruntimetensorflowserving
scottsun94/ray
Jul 2021 - Mar 2025
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Contributions:91 pushes, 15 branches in 3 years 7 months
apirayscalabledistributed-applicationshyperparameter
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