Patrick Buehler
Principal Machine Learning Engineer (Manager) at Motional
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolPatrick Buehler is a Principal Machine Learning Engineer and manager based in Boston, leading Motional’s Semantics team to deliver end-to-end perception and prediction features for self-driving vehicles. With a PhD from Oxford’s VGG under Prof. Zisserman and over a decade of industry experience at Microsoft and beyond, he blends deep research expertise in computer vision with production-grade ML engineering and deployment. He has a track record of scaling teams and code—growing Microsoft’s PyTorch Computer Vision Best Practices repo to 8,000+ stars—and has driven projects spanning traffic light and emergency-vehicle detection to visual semantic features for prediction. Equally comfortable mentoring and shipping, he pairs hands-on contributions (e.g., custom image annotation tooling) with strategic leadership across data acquisition, model training, evaluation, and on-car integration.
10 years of coding experience
12 years of employment as a software developer
PhD Computer Vision / Machine Learning, PhD Computer Vision / Machine Learning at University of OxfordExchange year Computer Science, Exchange year Computer Science at University of Massachusetts Amherst
English, German, French
Github Skills (6)
computer-vision10
ipywidgets10
jupyter-notebook10
image-annotation10
python10
machine-learning9
Programming languages (4)
Github contributions (5)
microsoft/computervision-recipes
Feb 2019 - Oct 2021
Best Practices, code samples, and documentation for Computer Vision.
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 18 reviews, 297 commits in 2 years 8 months
Contributions summary:Patrick's commits focused on implementing an image annotation widget using the ipywidgets library within the context of the computer vision-recipes repository, specifically for image classification tasks. The primary contribution involved the creation of a user interface (UI) for labeling images. The user also made several iterative updates to a notebook related to image annotation, refining the implementation. The code changes indicate the creation and integration of a custom annotation tool to facilitate image labeling.
pythonjupyter-notebookoperationalizationimage-classificationmicrosoft
Azure/ImageClassificationUsingCntk
May 2017 - Nov 2017
Contributions:15 commits in 5 months
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