Research
Paris / Zürich
Senior Research Scientist
Research learning systems intended to form useful representations of dynamic environments, retain context across time, and support reasoning and planning.
What you will do
- Research methods for learning useful representations from physical interaction and multimodal observation.
- Explore world models, memory, reasoning, and planning for agents operating in changing environments.
- Design rigorous evaluations of generalization, uncertainty, failure modes, and safety boundaries.
- Turn promising ideas into reproducible experiments and collaborate on embodied validation when appropriate.
- Communicate research clearly and contribute to external publication when approved.
What you bring
- 10+ years of relevant experience across advanced study, research, and technical leadership in machine learning, robotics, computer vision, reinforcement learning, or a related field.
- A PhD or equivalent demonstrated research depth, with an exceptional record of original, high-impact work.
- A track record of personally leading ambitious research programs from hypothesis through rigorous evaluation.
- Excellent Python and hands-on experience with PyTorch or JAX and modern training infrastructure.
- Deep knowledge of world models, multimodal learning, model-based reinforcement learning, generative sequence models, memory, or planning.
- The ability to work independently, challenge assumptions, and collaborate closely across research and engineering.
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