Benoit Chevallier-mames
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolBenoit Chevallier-mames is a security-focused engineering leader combining deep academic research (Ph.D. in Cryptography) with hands-on product development for widely used systems. He has worked across the defensive and offensive sides of security at organizations from smart-card leader Gemplus and the French cybersecurity agency DCSSI to Apple, where an obsession with details shaped his approach to product quality. Now leading a division at Zama, he drives teams at the intersection of software, ML and compilers to deliver privacy-preserving cloud and ML solutions using Fully Homomorphic Encryption. His practical contributions include improving developer workflows and CI/DevOps for Concrete ML, a prominent FHE-based privacy-preserving ML framework. Comfortable moving between theory, patents and production, he particularly enjoys operating at the frontier of cutting-edge cryptographic technologies. Based in Paris, he brings a rare blend of rigorous cryptographic expertise and product-minded engineering leadership.
5 years of coding experience
Mathematics & Physics, Mathematics & Physics at Classes Preparatoires aux Grandes EcolesEngineer Computer Science, Engineer Computer Science at CentraleSupélecPh.D. Cryptography, Ph.D. Cryptography at Université Paris Cité
English, French
Github Skills (11)
github-ci10
bash10
githubaction-workflow10
python10
cicd9
makefile9
gnu-make9
documentation8
jupyter7
data-science4
machine-learning3
Programming languages (10)
Github contributions (5)
zama-ai/concrete-ml
Jan 2022 - Jan 2023
Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks.
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:3 releases, 145 reviews, 426 commits in 1 year
Contributions summary:Benoit primarily focused on improving the development workflow and build environment of the Concrete ML project. Their contributions included enhancements to the Jupyter notebook execution scripts, the addition of nbqa for code quality checks, and the automation of license management, including checks for forbidden licenses. The user also introduced improvements to the documentation build process.
scientistspythonparticulartfhefhe
bcm-at-zama/huggingface-blog
Nov 2022 - Apr 2024
Public repo for HF blog posts
Contributions:1 review, 3 PRs, 55 pushes in 1 year 5 months
public-repopostsblog-posts
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