Mathieu Poumeyrol

Greater Paris Metropolitan Region France

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Summary

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Rockstar

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Top School

Mathieu Poumeyrol is a seasoned backend-focused software engineer based in Greater Paris with a track record of building and hardening large-scale server architectures across startups and product companies. With roles from CTO and Director of Cloud Engineering to Principal and now Distinguished Software Engineer at Sonos, he brings practical expertise in cloud migrations, performance monitoring, and resilient CI/CD for production systems. He has hands-on experience modernizing stacks—moving MySQL to MongoDB, introducing chef-managed infrastructure, and refining build/test pipelines for ML inference projects like Sonos/tract. A self-described geek, Mathieu pairs curiosity about systems (and even 60s space race trivia) with pragmatic problem solving that survives “cloud tantrums” and real-world failures. He mentors teams to balance elegant design with operational robustness and often contributes to the infrastructure and testing glue that keeps products shipping.

5 years of coding experience

13 years of employment as a software developer

Ingénieur spécialiste, Informatics and automatics, Ingénieur spécialiste, Informatics and automatics at ISIA - Mines de Paris

Ingénieur, science and technics, Ingénieur, science and technics at CentraleSupélec

Github Skills (12)

automation10

build-system10

automations10

rust10

cicd10

onnx9

tensorflow9

makefile9

artificial-intelligence8

neural-network8

testing8

artificial-neural-networks8

Programming languages (1)

Rust

Github contributions (5)

sonos/tract

Feb 2021 - Jan 2023

Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference

Role in this project:

MLOps Engineer

Contributions:2 reviews, 14 commits, 10 PRs in 1 year 11 months

Contributions summary:Mathieu's commits primarily focused on modifying build and testing scripts, and integrating configurations for the target operating system, indicating a strong involvement in the project's infrastructure and build process. They introduced changes to the CI/CD pipeline (.travis files), and scripts for the build process, as well as configurations for targeting specific platforms. Additionally, the user adjusted test scripts including testing for a specific version of the target. These changes suggest a focus on ensuring the project's continuous integration and deployment, specifically related to AI/ML inference tasks.

rust-libraryno-nonsenseself-containedrustdeep-learning

mathieupoumeyrolsonos/half-rs

Mar 2022 - Mar 2022

Half-precision floating point types f16 and bf16 for Rust.

Contributions:1 push in 1 day

f16floatingrustpointprecision

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