Michael Benayoun
Machine Learning Engineer at Hugging Face
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolMichael Benayoun is a Machine Learning Engineer based in Paris with nine years of experience specializing in training and fine-tuning Transformer models on custom AI accelerators. He has a strong track record at Hugging Face contributing to flagship open-source projects like transformers and optimum, where he enhanced torch.fx symbolic tracing and refactored core packaging to improve model export and ONNX weight handling. His background spans industry research at Huawei and hands-on production deployments—from smart-city chatbots to financial tooling—giving him both applied ML and software engineering depth. Michael combines low-level optimization skills with practical infra work, enabling efficient inference and training pipelines for large models. He studied across Grenoble and Montréal in computer science, physics and AI, which underpins his multidisciplinary approach to ML systems. Colleagues often rely on him to bridge model development, tooling, and deployment challenges that require both algorithmic insight and engineering rigor.
9 years of coding experience
8 years of employment as a software developer
Master's degree, Reseaux, Master's degree, Reseaux at National School of Computer Science and Applied Mathematics of GrenobleInternational Student, Intelligence artificielle, International Student, Intelligence artificielle at Polytechnique MontréalBachelor's degree, Physique et électronique, Bachelor's degree, Physique et électronique at Grenoble INP - PhelmaClasse préparatoire, MPSI / MP, Classe préparatoire, MPSI / MP at Lycée Marcelin Berthelot
Github Skills (16)
pytorch10
machine-learning10
transformer10
nlp10
deep-learning10
onnx10
python10
package-management9
gpt8
transformers8
optimization8
bert8
distilbert7
flax4
jax4
Programming languages (4)
Github contributions (5)
huggingface/optimum
Sep 2021 - Jan 2023
🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools
Role in this project:
Back-end Developer
Back-end DeveloperContributions:593 reviews, 36 commits, 99 PRs in 1 year 4 months
Contributions summary:Michael focused on modifying the core structure of the `optimum` library. Their primary contribution was refactoring the project to use namespace packages, making it easier to manage and organize the codebase. They updated the `setup.py` and `optimum/version.py` files. They also made improvements to the configuration files, and incorporated functionality to handle ONNX model weights more efficiently.
trainingoptimization-toolstransformersintelhardware
huggingface/transformers
Apr 2021 - Dec 2022
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Role in this project:ML Engineer
ML EngineerContributions:153 reviews, 30 commits, 67 PRs in 1 year 7 months
Contributions summary:Michael primarily contributed to the `transformers` repository, specifically focusing on enhancements to the `torch.fx` symbolic tracing feature. Their work involved implementing and refining symbolic tracing capabilities for various model architectures like BERT, ELECTRA, and T5, with subsequent additions for GPT-Neo, ALBERT, DistilBERT, and more. The user addressed shape issues during tracing and implemented a more scalable tracing approach and also added new models. Their efforts improved the model export and provided support for dynamic axes.
pythonbertspeech-recognitionstate-of-the-artflax
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