Jonathan Jin
Staff Machine Learning Engineer at Hinge
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolJonathan Jin is a Staff Machine Learning Engineer with 12 years of experience building production-grade ML platforms and AI infrastructure across consumer and research-focused companies. Currently leading model serving strategy and co-developing LLMOps capabilities at Hinge, he previously shaped cloud-native compute orchestration, SDKs, and governance at Spotify and built GPU-scheduling and distributed data-loading prototypes at NVIDIA. He combines hands-on systems engineering with product-minded platform design, advising nonprofits on technical roadmaps and managing small teams to deliver on mission-driven projects. Based in New York, Jonathan translates complex ML workflows into scalable, operational systems and has a track record of moving models from prototype to reliable service.
12 years of coding experience
9 years of employment as a software developer
Bachelor of Science (BS) Computer Science Economics, Bachelor of Science (BS) Computer Science Economics at University of Chicago
Chinese, Japanese
Stackoverflow
496reputation
35kreached
8answers
3questions
Github Skills (200)
testing10
stylegan10
hyperparameter-optimization10
automation10
automl10
gomock10
beam10
scheduler10
llm-inference10
api10
mode-line10
data-science10
apache10
llm10
notebook10
Programming languages (14)
Github contributions (5)
jinnovation/dotfiles
Dec 2013 - Nov 2022
Contributions:444 commits, 111 pushes, 7 branches in 9 years
jinnovation/rainy-image-dataset
May 2017 - Mar 2019
A mirror of Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, and John Paisley's set of synthetic rainy images.
Contributions:3 commits, 2 PRs, 8 pushes in 1 year 9 months
styleganhuangimage-processingsyntheticimage-classification
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