Guillaume Lagrange
Machine Learning Developer at Tracel Technologies
Montreal, Quebec, Canada
Summary
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Rockstar🎓
Top SchoolGuillaume Lagrange is a Machine Learning Developer in Montreal with eight years of experience building production-ready AI and software systems across imaging and embedded domains. He moved from instrumentation and control into software and AI, contributing machine-learning features at Teledyne DALSA before joining Tracel Technologies to focus on ML product development. A Mila Professional M.Sc. graduate with a B.Eng. in Automation, he blends rigorous academic training with hands-on engineering across C++, Rust, and systems-level tooling. Guillaume is an active open-source contributor to tracel-ai/burn, enhancing tensor quantization, ONNX op support, and autotune reliability—work that reflects a focus on efficient, portable deep learning runtimes. Colleagues know him for pragmatic problem-solving that bridges low-level performance work and higher-level ML workflows.
7 years of coding experience
6 years of employment as a software developer
Professional M.Sc., Computer Science, Professional M.Sc., Computer Science at Mila - Quebec Artificial Intelligence InstituteB.Eng., Automation Engineering, B.Eng., Automation Engineering at École de technologie supérieureDiploma of College Studies, Computerized Systems Technology, Diploma of College Studies, Computerized Systems Technology at Cégep Gérald-Godin
French, English
Stackoverflow
1reputation
0reached
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Github Skills (12)
tensorrt10
automatic-differentiation10
deep-q-learning10
deeplearning4j10
rust10
deep-learning10
tensor10
tensorflow10
operation10
onnx9
data-handling9
quantization9
Programming languages (3)
Github contributions (5)
tracel-ai/burn
Aug 2023 - Apr 2025
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 releases, 722 reviews, 545 PRs in 1 year 8 months
Contributions summary:Guillaume primarily focused on contributing to the core functionality of the `burn` deep learning framework, building upon the foundation established by the project's description. Their work included implementing and refining features such as a custom CSV dataset example, incorporating tensor quantization support, enhancing the handling of data representation, adding support for several ONNX operations and fixing issues with the autotune strategy. These contributions are critical to the framework's ability to efficiently manage, process, and dequantize tensors.
rustyburnndarraydeep-learningrust
laggui/image-search-scraper
Oct 2018 - Apr 2019
Contributions:47 commits, 20 pushes, 3 branches in 5 months
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