🧭 Spatial AI & SLAM Engineer

All open rolesAI🧭 Spatial AI & SLAM EngineerPalo Alto, CA (On-Site)/Full-timeApply nowShareAbout the roleDesign and deploy real-time spatial perception systems that allow humanoid and mobile robots to understand, navigate, and interact with complex 3D environments. You will work at the intersection of classical geometry, state estimation, and modern learning-based scene representations to build long-horizon world models that directly power manipulation and Vision-Language-Action (VLA) systems in the real world.Requirements01MS or PhD in Robotics, Computer Vision, Computer Science, or a related field—or equivalent industry experience02Strong background in SLAM, state estimation, and probabilistic sensor fusion03Deep understanding of 3D geometry, multi-view geometry, camera models, and calibration04Hands-on experience building perception systems for real robotic platforms05Experience with neural scene representations such as NeRFs, neural occupancy grids, or implicit SDFs06Proficiency in Python and C++ in Linux-based robotics environments07Experience working with large-scale datasets and long-running perception or learning experiments08Self-driven, systems-oriented, and excited about deploying perception on real robots09(+) Familiarity with Vision-Language-Action (VLA) or embodied AI systems10(+) Experience with tactile, force, or event-based sensors11(+) Background in Gaussian splatting, neural SDFs, or hybrid geometric-learning map representations12(+) Experience integrating perception outputs into manipulation or control pipelines13(+) Familiarity with Isaac Sim, MuJoCo, or photorealistic simulation environmentsDetails & responsibilities01Design and deploy real-time SLAM and state-estimation systems for humanoid and mobile robots02Build multi-sensor fusion pipelines combining RGB-D, stereo, LiDAR, IMU, and tactile sensing03Develop neural scene representations including NeRFs, neural occupancy grids, and signed distance fields04Bridge classical geometry-based perception with learning-based spatial models05Enable long-horizon 3D world modeling for manipulation and interaction tasks06Integrate perception outputs into Vision-Language-Action (VLA) systems07Improve robustness under occlusion, motion blur, lighting variation, and sensor noise08Support sim-to-real transfer using synthetic data generation and domain randomization09Collaborate closely with robotics, controls, and learning teams to close the perception-action loopCompensation & benefits01Competitive salary and meaningful equity02Comprehensive health, dental, and vision coverage03Work with world-class researchers and engineers in robotics and AI04High-ownership role with impact on core robot intelligence systems05Opportunity to define the future of real-world spatial perception and embodied AIInterested in this role?Applying takes a few minutes — you'll need an account to submit.Apply now