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About the Role
As a Research Scientist at Google DeepMind, you will be at the forefront of AI development, focusing on advancing AI to solve complex global challenges and accelerate high-quality product innovation. This role involves setting up large-scale tests, deploying promising ideas, and applying the latest theories to develop new products, processes, or technologies. You will work on real-world problems spanning machine learning, data mining, NLP, and more, with a specific emphasis on robotics problems and foundation model training. You will manage large volumes of multimodal data, optimize data mixtures for training frontier models, and contribute to the wider research community through sharing and publishing findings.
Responsibilities
- Drive data quality, acquisition, and labeling strategies, and oversee mixture optimization for robotics foundation models.
- Coordinate training runs, improve training recipes, and systematically hill-climb model performance against benchmarks.
- Build and maintain the software tools and processes required to iterate on research ideas quickly and verify data quality through robot policy training.
- Contribute to our wider research agenda, including reinforcement learning, vision-language-action modeling, world-action models, and simulation, working in a fast-paced, collaborative team environment.
Requirements
- PhD in a technical field or equivalent practical experience.
- Experience with algorithmic architectures, data sources, and training and inference techniques for generative multimodal models, especially for robotics applications (e.g., VLAs, WAMs).
- Experience optimizing models and systems (e.g., performance tuning, experimentation, and debugging).
- Practical experience in 'hill-climbing' model performance (e.g., iteratively improving training recipes and model benchmarks).
- Experience working with simulators and real-world robotic platforms (e.g., dexterous manipulation, multimodal sensing).
- Experience with benchmarking, different data sources, data labeling strategies, and data mixture optimization for robotics foundation models.
- A passion for bringing research from the lab to robust, real-world robotic systems.
- Proven ability to build and maintain the software tools for rapid iteration on research ideas.
- Experience with robot policy training using imitation learning and related techniques.
- Experience navigating the realities of pre-training.
- Enthusiasm about practical considerations such as data quality, mixture optimization, data labeling, systematic benchmarking, scaling ladders, performance hill-climbing.
Skills
- Algorithmic architectures
- Generative multimodal models
- Robotics applications
- VLAs
- WAMs
- Model optimization
- System optimization
- Performance tuning
- Experimentation
- Debugging
- Hill-climbing model performance
- Training recipes
- Model benchmarks
- Simulators
- Real-world robotic platforms
- Dexterous manipulation
- Multimodal sensing
- Benchmarking
- Data sources
- Data labeling strategies
- Data mixture optimization
- Robotics foundation models
- Software tools for research iteration
- Robot policy training
- Imitation learning
- Pre-training
- Data quality
- Scaling ladders
- Reinforcement learning
- Vision-language-action modeling
- World-action models
- Simulation
Education Level
- PhD in a technical field or equivalent practical experience.
About the Company
- 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.
- Google DeepMind is 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.
- Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.