Max Degroot is a software engineer with a decade of experience applying deep learning and ML to real-world products, currently based in Seattle. He has driven ML work across Amazon Alexa, Kindle search, and AWS Comprehend Medical—shifting from on-device search and QA models to scalable clinical NLP for unstructured health data. A Vanderbilt Math & CS graduate with hands-on research in computer vision and wearable devices, he bridges R&D and production engineering and has contributed evaluation tooling to the PyTorch ecosystem (notably implementing AP/mAP meters). Fluent in Python, Lua, C++ and Java, he’s equally comfortable prototyping novel models and leading technical improvements in shipped systems. His recent interests include AI’s effects on mental health and practical intersections of CS and healthcare.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.) Mathematics and Computer Science, Bachelor of Science (B.S.) Mathematics and Computer Science at Vanderbilt University
A lightweight library for PyTorch training tools and utilities
Role in this project:
ML Engineer
Contributions:7 commits, 1 PR, 4 comments in 3 days
Contributions summary:Max primarily focused on implementing and testing the `APMeter` and `mAPMeter` classes, essential tools for evaluating machine learning model performance in the context of object detection and classification tasks. Their contributions included writing the core code for these meters and creating unit tests to ensure their accuracy and reliability. Further, they addressed compatibility issues by incorporating support for Python 2 and making minor improvements to clarify the existing code.
Contributions:27 commits, 2 pushes, 1 comment in 1 month
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