Simon Alibert
Cofounder & CTO at UMA
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolSimon Alibert is a Cofounder & CTO based in Paris with a multidisciplinary background that blends actuarial rigor and practical machine learning applied to robotics and product-facing systems. After foundational roles in actuarial modeling and risk at major insurers, he transitioned to ML engineering—building Hugging Face's LeRobot and contributing end-to-end learning features for real-world robotic control. As a founder at UMA he combines product leadership with hands-on engineering, shipping models, data pipelines, and pricing/recommendation engines from prior freelance engagements. He is comfortable operating at the intersection of research and production, fluent in model implementation, dataset engineering and software refactors. Notably, his trajectory reflects a rare mix of regulatory-grade numerical modeling experience and open-source robotics ML contributions, enabling robust, auditable ML systems for physical products.
3 years of coding experience
4 years of employment as a software developer
Statisticien Actuarial Science, Statisticien Actuarial Science at Institut de Statistique de l'Université de Paris - ISUPMachine Learning Engineer Machine Learning AI, Machine Learning Engineer Machine Learning AI at Yotta Academymathematics physics and engineering, mathematics physics and engineering at Lycée Notre Dame de la Merci
French, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (10)
pytorch10
machine-learning10
robotics10
python10
modeling9
datasets9
trainings9
data-engineering8
mlops7
tensorflow6
Programming languages (4)
Github contributions (5)
huggingface/lerobot
May 2024 - Mar 2025
🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning
Role in this project:
ML Engineer
ML EngineerContributions:277 reviews, 189 PRs, 540 pushes in 10 months
Contributions summary:Simon's commits primarily focused on enhancing the "lerobot" project, particularly with the integration of end-to-end learning for robotics. The user made changes to the code, including installing fixes, running pre-commit commands, and refactoring code to support the project's objectives. This involved modifications to policy and dataset files, indicating work related to model implementation and data management for robotic applications.
aliberts/intergalactic-news
Oct 2023 - Sep 2024
Contributions:63 pushes, 2 branches, 8 tags in 10 months
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