Ryan Clough
Sr. Software Engineer, Machine Learning Infrastructure at Spotify
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolRyan Clough is a senior software engineer specializing in machine learning infrastructure with 12 years of experience building and operating scalable ML platforms. At Spotify he helped found the internal TFX/Kubeflow effort, ran the managed Kubeflow on Kubernetes, authored widely used "Golden Path" docs, and led onboarding and SLO work to dramatically improve ML developer productivity. Previously at Vimeo he moved models into production—building visual search and near-real-time tagging systems on GCP—and earlier roles focused on large-scale ETL and data ingestion. He combines a maker’s creativity and musician’s attention to craft with deep engineering rigor, regularly embedding with teams to solve diverse ML problems end-to-end. Colleagues cite his documentation and developer education as standout contributions that accelerate whole organizations.
12 years of coding experience
7 years of employment as a software developer
BS, Software Engineering, BS, Software Engineering at Rochester Institute of Technology
Stackoverflow
1,117reputation
72kreached
3answers
5questions
Github Skills (148)
parallel10
python10
hyperparameter-optimization10
deep-learning10
docker-container10
ray10
optimization10
llm-inference10
audio10
ai10
data-science10
reinforcement-learning10
tensorflow10
kotlin10
pytorch10
Programming languages (16)
Github contributions (5)
rclough/dagobah
May 2015 - Jan 2016
Contributions:48 pushes, 16 branches, 2 comments in 8 months
pythondagschedulerjobjob-scheduler
rclough/ray
May 2025 - Jul 2025
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Contributions:5 pushes, 2 branches in 1 month
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