Google DeepMind is looking to advance the state of the art in artificial intelligence, specifically in building interactive world models for embodied AI to power the next generation of helpful robots.
Requirements
- Knowledge of the latest in large machine learning research.
- A track record of building and training world models, and experience deploying these models in simulators or on real-world robots.
- Expertise in using large datasets with deep neural networks to make real robots useful.
- Expertise in 3D computer vision, computer graphics, physics simulation, image and video generation models.
Responsibilities
- Design, implement, train and evaluate large world 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 building towards breakthroughs in general purpose robotics and contributing towards our flagship Gemini Robotics models.
- Working with real robots in the lab to bring these breakthroughs to life in real hardware
- Generate creative ideas on how to improve the fidelity, interactivity, and generalization of world models, set up experiments and test hypotheses.
- Report and present research findings clearly and efficiently both internally and externally.
Other
- PhD in a technical field or equivalent practical experience.
- Work effectively with a large collaborative team with fast-paced agendas to meet ambitious research goals.
- A real passion for AI impacting real world robots!
- We value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact.
- We are committed to equal employment opportunities 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.
