Nicolas Patry - Machine Learning Engineer at Genesis AI

Nicolas Patry

Machine Learning Engineer at Genesis AI

Netherlands

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Summary

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Rockstar

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Top School

Nicolas Patry is a Machine Learning Engineer with 11 years of experience building high-performance ML systems and libraries, currently based in the Netherlands. He blends production-grade backend engineering in Python and Rust with deep ML know-how across computer vision, NLP and PyTorch, having driven performance and stability improvements in widely used projects like Hugging Face's Transformers, Diffusers and Tokenizers. At Hugging Face he maintained inference infrastructure and contributed safetensors support and model-loading optimizations that directly improved API and demo performance, and earlier led latency-sensitive Rust work for a Gmail Smart Compose product as CTO at Ottomate. His open-source contributions span core algorithmic work (matmul/backprop in a Rust ML framework), dataset ingestion at scale, and cross-platform system tooling, showing strength across low-level performance and high-level model engineering. Known for spotting and fixing performance bottlenecks, he combines research-rooted rigor from École Centrale Paris with hands-on delivery in production ML systems.

11 years of coding experience

15 years of employment as a software developer

2011 Applied Maths, 2011 Applied Maths at Ecole Centrale Paris

Bac S Mention bien, Bac S Mention bien at EABJM

French, English, Italian, Spanish, Japanese

Github Skills (69)

transformers10

operation10

python10

diffusion-models10

datasets10

deep-learning10

lora10

optimization10

tokenize10

event-handling10

data-engineering10

diffusion-probabilistic10

tokenizer10

performance-optimization10

optimisation10

Programming languages (16)

C++RustCHandlebarsGoHTMLJupyter NotebookCuda

Github contributions (5)

huggingface/safetensors

Sep 2022 - Jan 2023

Simple, safe way to store and distribute tensors

Role in this project:

DevOps Engineer & Python Developer

Contributions:48 releases, 148 reviews, 130 commits in 4 months

Contributions summary:Nicolas primarily focused on improving the build process and CI/CD pipeline of the project. They created and modified build scripts, particularly for Python wheel builds, source distributions, and Conda scripts. Furthermore, the user implemented a utility tool to convert models on the Hugging Face Hub to the safetensors format and added necessary modifications for better compatibility with models such as those used by Diffusers.

pythontensorflowdistributesafetensors

huggingface/text-generation-inference

Oct 2022 - Jan 2023

Large Language Model Text Generation Inference

Role in this project:

Back-end Developer

Contributions:23 releases, 860 reviews, 2 commits in 2 months

Contributions summary:Nicolas's contributions primarily focused on enhancing the server-side functionality, specifically implementing and utilizing safetensors for model loading within the text generation inference framework. They modified existing code to integrate and leverage safetensors, a more secure format for storing model weights. The code changes involve updating model loading mechanisms, introducing new dependencies (such as safetensors), and modifying existing code to leverage these improvements.

nlppytorchlanguage-modelbloombert

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