Robotics Autonomy Engineer - Safety

Job description

FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. About the Job Field AI is building the future of autonomy—from rugged terrain to real-world deployment. We’re on a mission to develop intelligent, adaptable robotic systems that operate beyond simulation and thrive in unpredictable environments. As our Robotics Autonomy Engineer – Safety, you’ll own and advance the independent safety layer that keeps our robots safe around people, equipment, and terrain no matter what the rest of the autonomy stack decides. You’ll be part of a deeply technical team advancing real-world robotic capabilities through cutting-edge research, simulation tools, and field validation. If building the guarantees that let robots earn trust in the real world excites you, and you want to work where your code hits the ground (literally)—this is your role. This is Field AI. What You’ll Get To Do Own and evolve the safety layer that runs independently of perception, planning, and learned policies, and extend it to new wheeled, legged, and humanoid platforms Build runtime monitors and collision avoidance backstops that check every commanded motion against the environment before it reaches the robot Enforce speed, zone, terrain, and proximity limits, and define the safe operating envelope for each platform and deployment Design fallback and minimal risk behaviors, from graceful slow down to safe stop, and the logic that decides when to trigger them Build watchdogs and health monitoring across sensors, compute, communication, and actuation, so the robot always knows when it can trust itself Lead hazard analysis and safety case development for new platforms and new deployments Verify the safety layer in simulation, hardware-in-the-loop (HIL) testing, and field trials, with coverage that grows with every deployment Work with planning, control, locomotion, and integration teams so the nominal stack plans and moves within the safety envelope What You Have Master’s degree or higher in Robotics, Computer Science, Electrical Engineering, or a related field, or a Bachelor’s degree with substantial hands-on experience on safety related autonomous systems 2+ years of experience developing safety, monitoring, or fallback systems for robots or autonomous vehicles Strong grounding in classical planning and control, such as collision checking and trajectory validation Experience writing deterministic, real time, resource bounded C++ for systems where correctness matters more than features Solid Python skills for tooling, analysis, and test automation in Linux-based environments A verification mindset: you think in terms of assumptions, failure modes, coverage, and evidence Familiarity with safety standards for mobile robots and autonomous systems (e.g., ISO 13482, ISO 3691-4, ISO 26262) Familiarity with robotics middleware such as ROS/ROS 2, and with robot sensors such as LiDAR, depth cameras, and IMUs The Extras That Set You Apart Functional safety experience in autonomous vehicles, industrial robots, or aerospace Experience with runtime assurance architectures that wrap a learned or complex controller Experience with formal or set based safety methods applied to real robots Experience defining operational design domains and monitoring when a system is outside them Experience with redundant sensing, safety rated hardware, or safety rated communication Experience taking a robotic product through safety assessment or certification Experience with legged or humanoid platforms, where balance and contact make safety envelopes harder to define