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. We are looking for creative thinkers with strong algorithm-design and programming skills that want to build the next generation of AI agents for and grounded in the physical world.

In this role, you will work in collaborative teams to invent algorithms and innovate on large foundation models such as Gemini Robotics. You will design prototype applications and work with real robots inside and outside the lab to manage real-world use cases. A strong algorithmic background in scalable machine learning (e.g., reinforcement learning/imitation learning; multimodal foundation models) and experience with real robots/robot simulation and training setups are 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.

• reinforcement learning
• imitation learning
• multimodal generative modeling
• training and inference
• vision models
• vision-language models
• video multimodal models
• simulators
• real-world robots
• dexterous manipulation
• multimodal sensing
• tactile sensing
• force sensing
• system implementation
• large real world data
• capture methodologies
• dataset design
• experimentation
• human action data
• vision-language-actions (VLAs)
• whole-arm manipulators (WAMs)
• algorithm design
• programming
• AI agents
• Gemini Robotics
• prototype applications
• robot simulation
• scalable machine learning
• multimodal foundation models
• robotics foundation models
• learning from simulation
• learning from demonstrations
• transformers
• video generation
• robot control
• humanoid robots
• machine learning
• deep learning
• data mining
• natural language processing
• hardware performance analysis
• software performance analysis
• compilers
• core search