Hui Miao
Software Engineer at Google
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolHui Miao is a seasoned software engineer with 10 years of experience building production-scale machine learning platforms at Google TFX and Google Brain, based in Mountain View. He has a strong background in recommender systems and personalization from leading technical work at Tmall/Alibaba and earlier research engineering at Samsung, combining large-scale data engineering with applied ML. Hui contributes to well-known open-source ML infrastructure—having implemented a bulk PutTypes API and data model extensions in Google's ml-metadata repository—bridging backend systems, storage design, and testing. He holds advanced computer science degrees from Seoul National University and the University of Maryland, and brings a research-informed approach to production reliability and metadata-driven ML workflows. An understated strength is his ability to translate research and standards work into scalable platform features that improve developer productivity and model reproducibility.
10 years of coding experience
3 years of employment as a software developer
Master of Science (MSc), Computer Science, Master of Science (MSc), Computer Science at Seoul National UniversityThe University of Maryland, College ParkSuzhou High SchoolBachelor of Engineering (BEng), Computer Engineering, Bachelor of Engineering (BEng), Computer Engineering at Shanghai Jiao Tong University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
api10
python10
apidoc10
back-end-development10
grpc9
testing9
data-modeling9
c-language8
cprogramming-language8
Programming languages (3)
Github contributions (5)
google/ml-metadata
May 2019 - Aug 2021
For recording and retrieving metadata associated with ML developer and data scientist workflows.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 releases, 5 reviews, 212 commits in 2 years 3 months
Contributions summary:Hui implemented core functionality related to the ML metadata storage, specifically focusing on a new `PutTypes` API to support bulk insertion of types. The code changes involved modifications to the data model (adding `ContextType`) and the server-side implementation for persisting and retrieving metadata. The user also contributed to the testing framework to ensure the new API and data model additions function correctly.
pythondata-sciencemachine-learningrecordingscientist
BrianSong/ml-metadata
Jul 2020 - Aug 2020
For recording and retrieving metadata associated with ML developer and data scientist workflows.
Contributions:2 pushes, 132 comments in 1 month
pythondata-qualitydata-sciencemlmachine-learning
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