Keshi Dai
Staff Machine Learning Engineer at Spotify
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolKeshi Dai is a Staff Machine Learning Engineer based in New York with 13 years of experience building data and ML infrastructure at scale, primarily at Spotify where they progressed from Senior Data Engineer to Staff ML Engineer. They specialize in productionizing machine learning systems and platform engineering, bridging research-quality models with reliable, large-scale deployment pipelines. Keshi's background includes senior roles in advertising and data engineering at MediaMath and eBay's Hunch, giving them deep experience in real-time data, recommender systems, and inference infrastructure. Holding a Ph.D. from Northeastern University and a bachelor's from Zhejiang Sci‑Tech, they combine rigorous research training with pragmatic engineering execution. Colleagues describe them as a technical multiplier who mentors teams while driving complex cross-functional initiatives that turn experimental models into measurable product impact.
13 years of coding experience
11 years of employment as a software developer
Bachelor, Bachelor at Zhejiang Sci-Tech UniversityPh.D., Ph.D. at Northeastern University
Github Skills (96)
notebook10
parallel10
python10
kubeflow10
hadoop10
python-client10
hyperparameter-optimization10
scheduling10
deep-learning10
automl10
extensible10
ray10
dependency-resolution10
optimization10
streaming10
Programming languages (9)
Github contributions (5)
daikeshi/keshi-dev
Aug 2019 - Dec 2022
Contributions:17 pushes, 1 branch in 3 years 5 months
daikeshi/pipelines
Jul 2019 - Feb 2021
Machine Learning Pipelines for Kubeflow
Contributions:8 pushes in 1 year 7 months
data-sciencemachine-learningmlopskedrokubeflow
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