Minimum qualifications:- PhD in Computer Science, a related field, or equivalent practical experience.
- Experience contributing to research communities or efforts, including publishing papers at conferences (e.g., NeurIPS, CoRL, ICML, ICLR).
- Experience working with simulators and robots.
Preferred qualifications:- Experience training neural networks using large datasets or simulation to improve real robot behavior.
- Experience in robot manipulation.
- Experience with Python programming.
About the jobIn this role, you will focus on building foundation models, such as advanced vision-language-action (VLA) models, which combine Gemini's world understanding with physical actions to provide direct robotic control. These include Gemini Robotics, our most advanced Gemini model for the physical world, and Gemini Robotics On-Device, our fastest Gemini model that functions without a data network.
These models allow robots to perform a broad range of tasks, respond interactively to their environment, achieve high dexterity, and reason over long, multi-step sequences. Beyond model building, we are committed to advancing general-purpose robotics, specifically in areas like agentic reasoning, real-world understanding, action generalization, human-robot interaction, dexterity, whole-body control, and continual learning. To deploy these innovations at scale, you will partner with key robotics companies to bring this intelligence to the physical world across a broad array of applications.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $211000 (USD) 15% bonus target bonus equity benefits
Learn more about benefits at Google .
Responsibilities- Design, implement, train, and evaluate large models and algorithms for robotic agents to make breakthroughs and unlock new robot capabilities.
- Write software to implement research ideas and iterate quickly.
- Participate in a wide variety of research, including learning from simulation, reinforcement learning, learning from demonstrations, vision-language-action (VLA) models, transformers, video generation, robot control, humanoid robots, and more.
- Work effectively with a large collaborative team with changing agendas to meet ambitious research goals.
- Generate creative ideas, set up experiments, and test hypotheses to report and present research findings clearly and efficiently both internally and externally.
