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About the Role
Lead efforts in developing novel algorithms and models for embodied AI and Artificial General Intelligence. Invent algorithms and innovate on large foundation models such as Gemini Robotics. Design prototype applications and work with real robots to address real-world use cases. Experience with scalable machine learning, real robots/robot simulation, and large-scale training setups are valued.
Responsibilities
- Design, train, and evaluate scalable algorithms for robotic agents, with a specific focus on post-training, self-improvement, and mastery.
- Leverage 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.
Requirements
- PhD degree in a technical field or equivalent practical experience.
- 2 years of experience in 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.
- 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 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.
Skills
- Reinforcement learning
- Mid-/post-training of foundation models
- Self-improvement in robotics
- Multimodal generative modeling
- Training and inference
- Vision-language/video
- Multimodal models
- Dexterous manipulation
- Multi-fingered hands
- Whole body control
- Multimodal sensing
- Large-scale systems implementation
- Algorithm design
- Programming skills
- Scalable machine learning
- Robot simulation
- Large-scale training setups
- Imitation learning
- Simulation-based learning
Experience Level
- 2 years of experience
Education Level
- PhD degree in a technical field
About the Company
- Artificial intelligence will be one of humanity’s most transformative inventions.
- At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users.
- We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
- We are pushing the boundaries across multiple domains.
- Our global teams offer varied learning opportunities and career pathways for those driven to achieve exceptional results through collective effort.