About Felix
Need robust ML pipelines or cutting-edge AI for your startup?
I am an AI researcher and engineer who bridges the gap between academic breakthroughs and production-ready systems. With publications at top-tier conferences (NeurIPS, ICLR) and hands-on experience transferring research to application, I help startups and innovative companies turn AI ideas into reliable, performant solutions.
How I can help you:
- Build cutting-edge ML POC: from data preprocessing to model prediction, I create scalable systems that use latest research advances.
- Implement Reinforcement Learning solutions: whether you're optimizing decision-making, or complex control systems, I bring research-grade RL expertise to real-world problems.
- Develop Evolutionary Algorithms: tackle complex optimization problems in a robust and scalable way with cutting-edge evolutionary approaches.
- Accelerate your AI R&D: leverage my research background to prototype novel solutions faster than traditional approaches.
What sets me apart:
Published researcher - Papers at NeurIPS, ICLR, and other top AI conferences
Research-to-application expertise - Beyond theory, provides practical insights on how to use latest AI research
Specialized in RL & Evolutionary AI - Deep expertise in developing and using state-of-the-art algorithms
Startup-friendly - Fast iteration, clear communication, pragmatic solutions
Typical deliverables:
- Technical audits and AI strategy consulting
- Proof-of-concept implementations
- ML pipelines
- Custom RL agents and training frameworks
- Evolutionary optimization systems
Whether you need someone to build your first ML infrastructure or explore advanced AI techniques like RL and evolutionary algorithms, I deliver research-quality work at startup speed.
English
Fluent
French
Native or bilingual
German
Basic
Remote only
Primarily works remotely
Experience
- InstaDeepSenior Research EngineerSOFTWARE PUBLISHINGOctober 2021 - Today (4 years and 8 months)Paris, FranceLeading our research effort on Inference strategies for Reinforcement Learning. Published an Oral paper at NeurIPS 2025.Research in RL for Combinatorial Optimisation. Published two NeurIPS papers on the topic.Research in Reinforcement Learning and Evolutionary algorithms (Quality Diversity). Published several papers in international conferences (ICLR, GECCO) and journals (JMLR, ACM). Developed reference QD research package in JAX (QDax).
- Polytechnique MontréalResearch internMarch 2020 - August 2020 (5 months)Reinforcement Learning for Combinatorial Optimisation. Developed a solver in Julia which combined Constraint Programming with RL. Results published at CPAIOR '21.
- Accenta.aiMachine Learning Research internENERGY AND UTILITIESSeptember 2019 - March 2020 (6 months)Île-de-France, FranceDevelop a POC tool for sensitivity analysis of an optimisation system for building energy management.
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Education
- MasterÉcole PolytechniqueÉcole Polytechnique is the most renowned and selective French Engineering school, driving top-notch research and innovation in the fields of science and technology since 1794. Relevant coursework: Third year: Computer Science (Machine and Deep Learning, Advanced Topics in Artificial Intelligence), Applied Mathematics (Monte Carlo simulation and stochastic processes, Art of Regression, Statistics in Action). Second year: Computer Science (Java, Website creation), Applied Mathematics (Random Effects Model, Control of Dynamic Models, Approximation & Optimization), Physics (Quantum Mechanics, Statistical physics), Economics. Activities : • Chairman, Binet Fun, the very fast-growing Nautical Society. • Vice-Chairman, Cabinet Start-Up, the Entrepreneurial Society. • Regular participant, X-Para, the Skydiving Society.
- Preparatory Class, Physics and MathematicsCollège Stanislas Paris2017Two-year intensive university-level program preparing for the national competitive exam for entrance to the top French engineering schools. Relevant coursework: Physics, Mathematics, Chemistry, Computer Science, Philosophy, English.