Role
As a Senior Research Scientist focused on Robotic Foundation Models, you will be responsible for the design and implementation of systems that enable the training, deployment, and utilization of large-scale AI models for robotics. You will guide technical direction, mentor engineers, and ensure the development of robust, scalable ML models required to make robots significantly more capable in real-world environments. Your work will empower both internal teams and external partners by providing accessible tools and infrastructure for injecting advanced machine learning techniques into robotic applications.
How your work moves the mission forward
- Lead the design and implementation of infrastructure and architecture of large-scale robotic foundation models.
- Oversee the training and deployment of robust ML models for high-performance robotic applications.
- Empower ML researchers and engineers with accessible tools and infrastructure for developing and applying AI techniques in robotics.
- Collaborate with product and engineering teams to define infrastructure requirements and deliver successful solutions for partners and customers.
Skills you will need to be successful
- PhD in Computer Science / Engineering with a specialization in Machine Learning and / or Robotics.
- Experience collaborating on medium to large software projects for at least 4 years.
- Experience in programming Python / C++ and machine learning frameworks (Tensorflow, JAX).
- Demonstrable experience with offline Reinforcement Learning / Imitation Learning in a robotics context.
- Proven ability to work with a team, setting directions and driving towards solutions.
Skills that will differentiate your candidacy
- Academic track record of publications in the field of offline Reinforcement Learning / Imitation Learning in Robotics.
- Experience with Robotic Foundation Models / Vision-Language-Action Models.
- Experience with Online Reinforcement Learning and / or Computer Vision for Robotics.
- Experience with deploying ML services at scale, e.g., via cloud computing and containerization (Google Cloud, Docker, Kubernetes), databases (SQL, no-SQL), and service-oriented architecture frameworks.