Responsibilities

• Lead the design and deployment of expert and generalist policies that enable industrial targeted tasksets to be enacted.
• Drive the design of task policies using techniques such as hierarchical planning, reinforcement learning, or hybrid methods.
• Develop real-world and simulation-based datasets for benchmarking and validation; guide sensor selection and system integration.
• Collaborate cross-functionally with embedded, hardware, and systems engineers to bring scalable solutions from research to production.
• Stay current with the state of the art in robotics, Edge AI, and self-supervised learning — and guide the team in adopting innovative technologies.
• Contribute to the broader AI platform architecture, CI/CD pipelines, and MLOps practices.

Responsibilities

• Lead the design and deployment of expert and generalist policies that enable industrial targeted tasksets to be enacted.
• Drive the design of task policies using techniques such as hierarchical planning, reinforcement learning, or hybrid methods.
• Develop real-world and simulation-based datasets for benchmarking and validation; guide sensor selection and system integration.
• Collaborate cross-functionally with embedded, hardware, and systems engineers to bring scalable solutions from research to production.
• Stay current with the state of the art in robotics, Edge AI, and self-supervised learning — and guide the team in adopting innovative technologies.
• Contribute to the broader AI platform architecture, CI/CD pipelines, and MLOps practices.