François Leblanc is a Senior Engineer specializing in Developer AI with over a decade of experience building data-driven solutions for the Canadian government and industry. He blends strong Python engineering, computer vision, GIS and cloud expertise to move ML prototypes into production—most recently shaping data and developer AI efforts at Shopify. His background spans applied research (bird counting from aerial imagery, NLP for public consultation) to production data platforms and secure Azure environments used by 60+ analysts, demonstrating both technical breadth and operational rigor. An active hacker and open-source contributor, he built and packaged utilities like an automated face-cropping tool for batch image processing, reflecting a focus on usability and deployability. Based in Gatineau, Québec, he pairs a scientific foundation in geology/physics with a practical data science certificate, bringing curiosity and cross-disciplinary thinking to complex policy and product problems.
10 years of coding experience
8 years of employment as a software developer
Data Science Certificate Sciences and Information Technologies, Data Science Certificate Sciences and Information Technologies at University of California, Irvine Division of Continuing Education
Bachelor of Science (B.Sc.) Geology Physics, Bachelor of Science (B.Sc.) Geology Physics at University of Ottawa
:relieved: Automatically detects and crops faces from batches of pictures.
Role in this project:
Full-stack Developer
Contributions:13 releases, 12 reviews, 250 commits in 6 years 10 months
Contributions summary:François primarily contributed to the development of an automated face cropping tool. Their work includes the initial implementation of the `autocrop.py` script, adding features like CLAHE and underexposure correction, and refactoring the code for better readability and organization. The user also added functionality to handle CLI arguments and package the project for PyPI, indicating a focus on both the core image processing functionality and the project's usability and deployment. The commits also involved changes to test suite and the use of a transparent image.
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