Requirements:
- PhD degree in a technical field or equivalent practical experience.
- 2 years of experience with reinforcement and imitation learning, multimodal generative modeling, training and inference, and vision/vision-language/video multimodal models.
Nice to haves:
- Experience working with simulators and real-world robots, esp. dexterous manipulation, as well as multimodal sensing (e.g., tactile, forces).
- Experience implementing systems and working with large real world data.
- Experience with capture methodologies, dataset design, experimentation, and incorporation of captured human action data into vision-language-actions (VLAs) or whole-arm manipulators (WAMs).
- Passion for bringing research from the lab to real-world robotic systems.
What you'll be doing:
- Design, implement, train, and evaluate large models and algorithms for robotic agents. Make breakthroughs and unlock new robot capabilities.
- Write software to implement research ideas and iterate quickly.
- Work effectively with a large collaborative team with changing agendas to meet ambitious research goals.
- Develop methodologies and design and conduct experiments for incorporating scalable data sources, especially human data with or without capture devices into our robotics foundation models.
- Leverage your broader expertise to participate in a wide variety of research: learning from simulation, reinforcement learning, learning from demonstrations, vision-language-action models, transformers, video generation, robot control, humanoid robots and more.
Perks and Benefits:
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.