Daiyi Peng
Software Engineer at Google
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolDaiyi Peng is a software engineer and engineering leader with nearly a decade in large-scale search, ML platforms, and distributed systems, currently contributing to Google's Brain AutoML team in Mountain View. He has a track record of architecting and delivering high-impact projects at Microsoft and Google—ranging from per-document indexing and superfresh news pipelines that cut latency from minutes to seconds, to a mixed-language ML experimentation system that accelerated feature iteration in Bing by 10x. Daiyi blends hands-on systems programming with people leadership, having built and led teams that shipped next‑gen ranking and ML infrastructure used across search and Office. He is an active open-source contributor (notably to Microsoft’s Napa.js multi-threaded JavaScript runtime) and favors pragmatic, performance-minded designs that enable rapid experimentation. With an academic background in computer science from Sichuan University, he focuses on the intersection of people and technology to turn complex research and engineering challenges into production impact.
10 years of coding experience
10 years of employment as a software developer
Master, Computer Science, Master, Computer Science at Sichuan University
Github Skills (10)
typescript10
javascript10
typescripts10
typescript-types10
runtime-environment9
runtimes9
run-time9
nodejs9
runtime-compilation9
multithreading8
Programming languages (5)
Github contributions (5)
microsoft/napajs
Dec 2016 - Dec 2017
Napa.js: a multi-threaded JavaScript runtime
Role in this project:
Back-end Developer
Back-end DeveloperContributions:45 commits, 28 PRs, 23 pushes in 1 year
Contributions summary:Daiyi contributed to the Napa.js runtime by modifying header files related to the API and modules. They also addressed compile sequence issues within the @napajs/metrics module, which involved TypeScript and metric providers. Furthermore, the user integrated changes related to vineyard by extracting object models into a separate TS file, implementing a request logger, and replacing counters with metrics. Additional contributions include modifications to transport-related files.
javascriptnapajsmultithreadingnodejsruntime
google/pyglove
May 2022 - Jan 2023
Manipulating Python Programs
Contributions:10 releases, 105 commits, 8 PRs in 8 months
pythonautomlevolutionmachine-learningmeta-learning
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