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Develop and maintain high-performance firmware and electronics for a dexterous robotic hand, integrate multi-modal sensors and sensor fusion, own system characterization and troubleshooting, and manage compliance and certification for deployment.

Integrate and deploy AI models on customer robotic platforms, adapt training and deployment pipelines, diagnose integration and perception issues, support on-site and remote deployments, coordinate across teams, and track deployment KPIs to scale proofs-of-concept into production.

Develop, deploy, and test infrastructural solutions for teleoperation and autonomous operation in dexterous robotic manipulation; lead a team in robotic control software development.

Work with robotics and AI teams to develop, deploy, and test teleoperation and learning infrastructure for dexterous manipulation; contribute code, debug systems, design/test simple hardware/software solutions, and collaborate cross-functionally.

The Head of Systems leads the technical evolution of robotics and AI platforms, enforcing architectural standards, ensuring reliability, and driving software certification.

As an AI Research Engineer, you will develop AI models for robotics, manage data processes, and ensure deployment efficiency. You'll collaborate closely with the robotic hardware teams and oversee various stages of model training and evaluation.

The Forward Deployed Engineer will implement AI solutions, manage technical projects, support deployments, and communicate with clients to adapt technology for diverse tasks.

The AI Research Scientist will develop AI models for robotics, manage data processes, collaborate with teams, and write Python code.

Lead research and implementation of large-scale, multi-task foundation models for dexterous robotic manipulation; manage the data flywheel from specification through collection, training, and real-world evaluation; fine-tune and specialize models; write maintainable Python deep-learning code; and collaborate with Robotics and Hardware teams to deploy models on real robots while co-leading AI engineering efforts.

Lead development of large-scale, multi-task robotic foundation models and manage the data flywheel: specification, collection, training, and real-world evaluation. Implement model specialization and fine-tuning, write production-quality Python for deep learning, and collaborate with robotics and hardware teams to deploy on real robots.