Member of Technical Staff - Robotics (Manipulation or Navigation)

About Dimensional Dimensional is building the foundation for physical intelligence in general-purpose robotics. We develop a unified framework that enables robots to perceive, reason, learn, and act across diverse real-world environments and embodiments. Dimensional’s mission is to make physical intelligence programmable, scalable, and accessible -- accelerating the development of generalist robots that can adapt, learn, and perform reliably in the real world. Our platform sits between robot hardware and AI models, providing a modular, composable architecture for training and deploying robotic intelligence at scale. By abstracting hardware differences and standardizing core capabilities—such as perception, spatial understanding, decision-making, and control—Dimensional allows developers and partners to build, transfer, and operate robotic skills efficiently across platforms. About This Role We’re looking for full-stack roboticists to own either manipulation or navigation systems end to end. These roles require strong theoretical grounding combined with real-world deployment experience. You’ll be working on robotic arms, mobile robots, and/or legged systems, helping take advanced robotics capabilities from lab-quality to production-ready. Core Responsibilities Design and implement robotic manipulation and/or navigation systems. Deploy and operate robotic systems on real-world hardware. Work across perception, planning, control, and end-to-end software integration. Debug, iterate, and improve real-world robotic behavior in production environments. Collaborate closely with software and infrastructure teams to deliver robust, integrated systems. What We Look For Relevant industrial or research experience in SLAM, Motion Planning, Controls. Experience deploying robotics systems. Field Robotics or Systems Engineering is highly regarded and prioritized. Comfort working across the full robotics stack, from perception and planning through control and system integration. Preferred Qualifications Educational background from leading robotics or computer science programs (e.g., MIT, CMU, Penn, Caltech, or equivalent institutions). Industry experience working with robotic arms, mobile robots, quadrupeds, or similar robotic platforms. Demonstrated experience transitioning robotic systems from prototype or research stages into production environments. #J-18808-Ljbffr