Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Lead the full product development cycle for dexterous robotic end-effectors, from concept and prototyping through integration and testing. Define system architectures, use cases, performance requirements, and packaging in collaboration with cross-functional teams. Evaluate grippers, sensors, and data-collection devices while supporting robotic hardware assembly, integration, and testing. The role covers systems ranging from two-finger grippers to multi-fingered humanoid hands and teleoperation training devices.

Designs and tests robotic hardware from overall system architecture through detailed components and assemblies. Responsibilities include developing concepts, defining requirements and packaging, creating 3D CAD designs and drawings, coordinating with vendors and manufacturers, and supporting assembly, integration, and testing. The role requires expertise in mechanical engineering, structural analysis, electromechanical integration, and complex robotic systems, with preferred experience in optimized structures, actuators, end-effectors, and high-volume manufacturing.

Lead testing and validation of robotic systems across simulation and physical robot environments. Define system- and unit-level test strategies, distribute test cases, execute tests, report results, develop testing and reporting utilities, and manage software version approval for field deployment. Collaborate closely with Controls, Autonomy, Integration, and Simulation teams.

Integrate, debug, test, and deploy robotic systems across power, actuation, networking, sensing, kinematics, motion planning, perception, and control. The role includes commissioning systems, developing test plans, integrating third-party components, deploying field applications, supporting customer integrations, participating in design and code reviews, and maintaining technical documentation. Collaboration with Controls, Hardware, and Autonomy teams is central to ensuring system performance and reliability.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

The Motion Planning & Controls Engineer will develop software for robot motion, implementing algorithms for optimized control and ensuring performance and safety.

Develop and maintain infrastructure for software development and AI operations, manage CI/CD pipelines, and automate configurations using various tools.

Build and own robot autonomy systems spanning task, behavior, path, and trajectory planning. Design long-horizon behavior architectures with recovery and operator handoff, coordinate multiple robots, integrate LLM/VLM reasoning safely, and define interfaces between learned policies and classical planners. Evaluate performance through simulation, log replay, regression testing, and real-robot field operation while collaborating across perception, controls, simulation, and platform teams.

Design, build, and operate ML infrastructure powering data, compute, artifacts, and orchestration across cloud and on-prem. Own backend services, storage, observability, security, and developer tools; collaborate with cloud/compute providers and lead reliability and scaling efforts.

Design and develop performant mathematical models of robots, manipulators, and environments; integrate simulation into CI/CD; balance fidelity and compute; collaborate with simulation, motion planning, controls, field ops and intelligence teams.