At Google DeepMind, the business problem is to advance the state of the art in artificial intelligence, specifically in enabling computers to understand and interact with user interfaces in a human-like manner, to unlock a wide range of agentic capabilities.
Requirements
- Experience with multi-step reinforcement learning
- Experience with post-training generative models
- Understanding of model training, evaluation metrics
- Experience with designing and analyzing machine learning experiments
- Ability to design and build evaluations
- PhD or relevant experience in computer science related field
- Adaptability: The field is evolving rapidly, requiring a willingness to learn new technologies and approaches
Responsibilities
- Making core contributions to post-training in Gemini that advances the frontier of what digital agents can do and is deployable into production
- Identifying model areas of improvement and owning work related to training and evaluating UI Control agents across various digital environments
- Multi-step reinforcement learning in multimodal, digital environments
- Research that improves the ability of the agent to handle more complex tasks or incorporate more user interaction
- Developing and contributing new evaluation methodologies
- Data Enhancement: Adding new data to post-training mixtures in Gemini
- Self-Improvement: Exploring methods such as online exploration and reinforcement learning
Other
- PhD or relevant experience in computer science related field
- Ability to work across the research stack to see their work through
- Willingness to learn new technologies and approaches
- Commitment 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
- Ability to push the boundaries of AI research related to computer use models
