Research Scientist, Robotics RL, DeepMind

• Design, train, and evaluate scalable algorithms for robotic agents, with a specific focus on post-training, self-improvement, and mastery.
• Leverage your experience to participate in a wide variety of other research themes in the context of robotics foundation models and physical agents (e.g. VLAs, WAMs, imitation learning, simulation-based learning, whole body control, dexterity, and more).
• Develop scalable research pipelines and write robust software to test hypotheses quickly and conduct research at pace.
• Collaborate within a fast-paced team to execute ambitious research goals.
• Generate creative ideas, set up experiments and test hypotheses, reporting and presenting research findings clearly and efficiently both internally and externally.

Minimum qualifications:

• PhD degree in a technical field or equivalent practical experience.
• 2 years of experiencein reinforcement learning or other techniques for mid-/post-training of foundation models and self-improvement in robotics, and other areas such as multimodal generative modeling, training and inference, vision-language/video, or other multimodal models.

Preferred qualifications:

• Experience working with simulators and real-world robots, esp. dexterous manipulation including multi-fingered hands or whole body control, as well as multimodal sensing (e.g. tactile).
• Experience deploying the above models and algorithms on real-world systems.
• Experience implementing large-scale systems and working with large real world data.
• A passion for bringing research from the lab to real-world robotic systems.

• PhD degree in a technical field or equivalent practical experience.
• 2 years of experiencein reinforcement learning or other techniques for mid-/post-training of foundation models and self-improvement in robotics, and other areas such as multimodal generative modeling, training and inference, vision-language/video, or other multimodal models.