Jeffery Kinnison
Senior Machine Learning Engineer at Rubrik
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJeffery Kinnison is a Senior Machine Learning Engineer with 11 years of experience marrying research-grade computer vision and scalable ML systems, currently based in Seattle and working at Rubrik. A doctoral candidate from the University of Notre Dame’s CVRL, he specializes in model selection, hyperparameter optimization, and biologically-inspired learning, with applied work spanning neuroscience and the digital humanities. He has productionized ML tooling and MLOps features—contributing to Ludwig by improving hyperparameter tuning integrations, dataset handling, and LightGBM trainer performance—showing fluency across core pipelines and operational infrastructure. His background includes developing neuroscience-focused tools for exascale supercomputing at Argonne and teaching CS courses, reflecting both deep technical rigor and experience communicating complex ideas. Collectedly, he bridges academia and industry, turning advanced research into reliable, maintainable systems.
11 years of coding experience
12 years of employment as a software developer
Bachelor of Arts - BA, Computer Science and English, Bachelor of Arts - BA, Computer Science and English at Clemson UniversityMaster of Science - MS, Computer Science and Engineering, Master of Science - MS, Computer Science and Engineering at University of Notre Dame
English, French
Stackoverflow
11reputation
1kreached
1answer
1question
Github Skills (18)
pytorch10
python10
machine-learning10
llm10
lightgbm10
ray10
data-science9
serialization9
apidoc9
data-serialization9
api9
natural-language-processing8
data-engineering8
tornado6
websocket6
Programming languages (7)
Github contributions (5)
ludwig-ai/ludwig
Jul 2022 - Jan 2023
Low-code framework for building custom LLMs, neural networks, and other AI models
Role in this project:
Back-end Developer / MLOps Engineer
Back-end Developer / MLOps EngineerContributions:199 reviews, 18 commits, 107 PRs in 6 months
Contributions summary:Jeffery contributed to the server-side logic of the Ludwig framework by implementing JSON and NumPy encoding for the server and integrating Ray Tune callbacks into hyperparameter optimization. Their work included enhancing the performance of the LightGBM trainer by repartitioning datasets, along with updating the framework to enable dataset window autosizing. The user also updated the exception messages and made several improvements to the sequence decoder and its tests. These improvements suggest the user contributes to both the core machine learning pipeline and the operational aspects of the project.
fairness-mlpythonframework-learningdeep-learning-frameworknatural-language-processing
jeffkinnison/tesserae-v5
May 2018 - Apr 2022
Contributions:6 PRs, 92 pushes, 7 branches in 3 years 11 months
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