Research Scientist, Robotics, DeepMind

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. For this position, we are especially looking for individuals who have experience with approaches for mid-/post-training for robotics foundation models, including reinforcement learning and related techniques that enable agents to self-improve and achieve mastery. This includes experience with the use of RL to train robot policies in simulation and in the real world. Experience with such techniques in the context of general multimodal frontier models (e.g., LLMs, VLMs, video models) and agentic systems is also highly valued. 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 diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Design, implement, train and evaluate large models and algorithms for robotic agents. Make breakthroughs and unlock new robot capabilities. Write software to implement research ideas and iterate quickly. Work effectively with a large collaborative team with changing agendas to meet ambitious research goals. Develop methodologies and design and conduct experiments for incorporating scalable data sources, especially human data with or without capture devices into our robotics foundation models. Leverage your broader expertise to participate in a wide variety of research: learning from simulation, reinforcement learning, learning from demonstrations, vision-language-action models, transformers, video generation, robot control, humanoid robots and more.

Minimum qualifications: PhD degree in a technical field or equivalent practical experience. 2 years of experience with reinforcement and imitation learning, multimodal generative modeling, training and inference, and vision/vision-language/video multimodal models. Preferred qualifications: Experience working with simulators and real-world robots, esp. dexterous manipulation, as well as multimodal sensing (e.g., tactile, forces). Experience implementing systems and working with large real world data. Experience with capture methodologies, dataset design, experimentation, and incorporation of captured human action data into vision-language-actions (VLAs) or whole-arm manipulators (WAMs). Passion for bringing research from the lab to real-world robotic systems.