Research Scientist, Multisensor Robotics & Dexterity

In this role, you will spearhead the creation of innovative models and algorithms for physical AI agents. We need inventive problem solvers with high-level programming skills to design agents that are deeply integrated with the real world. You will collaborate to evolve foundation models, test prototypes, and apply findings to actual robotics hardware. Expertise in reinforcement learning, multimodal models, and large-scale training is highly desirable.

Key responsibilities:

• Architect and train advanced models to expand the functional limits of robotic systems.
• Develop high-quality code to prototype and refine research concepts rapidly.
• Contribute effectively within dynamic, cross-functional teams to achieve high-impact goals.
• Apply specialized knowledge in core robotics domains, including:
• Sim-to-real transfer and reinforcement learning techniques,
• Imitation learning, VLA models, and generative architectures.
• Reactive fast-feedback low level controllers
• Propose novel ideas and communicate experimental results clearly to both technical and general audiences.
• Handle real-world hardware challenges, focusing on complex manipulation and advanced sensor integration.

• A PhD in a relevant quantitative field or significant professional research experience.
• Deep theoretical understanding of algorithmic frameworks like:
• Advanced reinforcement and imitation learning methodologies.
• Multimodal generative modeling and efficient inference systems.
• Scaling large-scale vision-language or video foundation models.

• Background in building large-scale data pipelines and production-ready systems.
• A strong drive to transition academic research into tangible robotic impact.