Jean-frédéric Fontaine

Machine Learning Engineer at Can-Ex Technologies

Quebec, Quebec, Canada
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Summary

👤
Senior
🎓
Top School
Jean-frédéric Fontaine is a Machine Learning Engineer with nine years of experience building and deploying production ML pipelines and embedded IoT software across North America. He has delivered mission-critical edge systems and backend services—implementing OTA updates, guaranteed data transmission, and protobuf-based APIs—while maintaining a modular, object-oriented C++ codebase and Python backends. He led the industrialization of a real-time computer vision weld-inspection system from prototype to Kubernetes-orchestrated production, and earlier contributed denoising and testing pipelines to scientific imaging software. Comfortable at the intersection of research and production, he has applied deep learning in domains from autonomous driving to EEG analysis and collaborated with neuroscientists to inform model design. A resilient problem-solver and clear communicator, he prioritizes team success and long-term maintainability over quick fixes. Based in Quebec, he combines embedded systems pragmatism with ML engineering rigor to turn complex prototypes into scalable deployments.
code9 years of coding experience
job6 years of employment as a software developer
bookBachelor's degree, Computer Software Engineering, Bachelor's degree, Computer Software Engineering at École Polytechnique de Montréal
bookPsychology, Psychology at Université de Montréal
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Github Skills (65)

python9
deep-learning9
machine-learning9
docker-container8
python-bindings8
tensorflow8
openvpn8
neural-network7
data-science7
pki7
dockerhub7
docker7
elk6
uncrustify6
jupyter-notebook6

Programming languages (6)

C++ShellPerlSvelteJupyter NotebookPython

Github contributions (5)

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tugu9/boneRepository

Jul 2020 - Aug 2020

Contributions:174 pushes, 8 branches in 1 month
Adrimeov/snakeAI

Oct 2018 - Apr 2020

Contributions:31 pushes, 1 branch in 1 year 7 months
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Jean-frédéric Fontaine - Machine Learning Engineer at Can-Ex Technologies