This role is deeply hands-on with real robot hardware, leveraging your expertise across vision-language-action (VLA) models, diffusion models, reinforcement learning, and dexterous manipulation.
What we’re looking for:
- PhD or Master's in Robotics, AI, or related fields
- Strong expertise in learning-based dexterous manipulation (multi-fingered grasping, task-oriented manipulation)
- Practical experience with running real-time controllers on robotic hardware
- Deep knowledge of diffusion models, transformers, CVAEs, normalizing flows
- Experience working with ROS, PyTorch, and Python
- Familiarity with vision-language models (VLA/VLMs/LLMs) for robotic planning or failure detection
- Bonus: experience with synthetic data generation, simulation environments, teleoperation systems
- Join a high-calibre team (ex-ETH / ex-NVIDIA founders) backed by significant investment (Seed + Series A secured)
- Work at the intersection of simulation, reinforcement learning, and robotics hardware
- Contribute to next-generation humanoid robots without reliance on traditional imitation learning paradigms