about 2 hours ago
Remote, Worldwide +2 moreSenior / Staff+
Responsibilities
- Design, implement, train, and evaluate large models and learning algorithms for robotic agents.
- Develop vision-language-action architectures connecting multimodal perception with physical control.
- Investigate reinforcement and imitation learning methods for complex objectives.
- Build scalable methods for incorporating diverse data into foundation models.
- Design capture methodologies, datasets, and evaluation protocols for embodied learning.
- Develop simulation environments and conduct experiments on physical robotic platforms.
- Explore planning and search over action trajectories.
- Prototype new capabilities in dexterous and mobile manipulation.
- Write robust research software and distributed training infrastructure.
- Collaborate with teams to translate research ideas into reliable systems.
- Communicate results through reports, open-source releases, and publications.
Requirements
- Profound understanding of machine learning, reinforcement learning, or robot learning.
- Deep expertise in areas like reinforcement learning, computer vision, or robotics.
- Experience training and evaluating modern deep learning models.
- Substantial experience training large models across multiple computational nodes.
- Strong software engineering and algorithm-design skills, primarily in Python.
- Deep experience with a modern deep learning framework, preferably JAX.
- Ability to design and analyze machine learning experiments with statistical rigor.
- Experience implementing research ideas and iterating quickly across various domains.
- Strong communication and leadership abilities for cross-disciplinary collaboration.
- Ability to document research findings and contribute to technical reports.
Benefits
- Competitive compensation.
- Career growth and learning opportunities.
- Flexibility and ownership.
- Collaborative and innovative culture.
- Opportunity to work on impactful AI projects.
- International environment and talented teams.