Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
About UsWe are looking for Research Scientists to join the Robotics team whose mission is to build “Embodied AI” - a robot brain capable of whole-body, dexterous, general and useful physical actions - to improve the lives of billions of people in the physical world.
The RoleResearch Scientists work on a diverse and stimulating range of projects including: inventing algorithms and prototype applications, working with real robots in the lab and outside the lab tackling real world use cases. Research Scientists work in large collaborative teams to make cutting edge breakthroughs to advance Robotics AI. We believe large foundation models will transform general purpose Robotics like with our Gemini Robotics models. This role will involve working with a diverse multi-functional team that builds the future of robotics.
Key responsibilities:
- 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.
- Leverage your 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.
- Work effectively with a large collaborative team with fast-paced agendas to meet ambitious research goals.
- Generate creative ideas, set up experiments and test hypotheses. Report and present research findings clearly and efficiently both internally and externally.
In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
- PhD in a technical field or equivalent practical experience.
- Knowledge of the latest in large machine learning research.
In addition, the following would be an advantage:
- Experience working with simulators and real-world robots.
- Expertise in using large datasets with deep neural networks to make real robots useful.
- A real passion for AI impacting real world robots!
The US base salary range for this full-time position is between $166,000 - $244,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
Top Skills
What We Do
We’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).
Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.
We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.









