FieldAI - Senior/Staff Robotics Autonomy Engineer-Planning and Control (Federal)

Remote - Irvine, CA$70k - $300k+ Equity1mo ago

Remote Staff NA Robotics Public Sector Automation Engineer C++Linux Python

Requirements

• PhD degree in Robotics, Computer Science, Electrical Engineering, or a related field with 2+ years of industry or applied research experience or MS degree in a related field with 4+ years of relevant experience, or BS degree in a related field with 8+ years of relevant experience. • Strong understanding of motion planning, trajectory generation, and control systems. • Experience developing algorithms for one or more robotic systems (wheeled, legged, wheeled-legged, humanoid). • Familiarity with motion planning libraries like OMPL, MoveIt, Nav2 stack etc • Solid programming skills in C++ and Python on Linux-based systems. • Familiarity with robotics middleware such as ROS/ROS 2. • Experience with robot sensors including LiDARs, stereo/depth cameras, IMUs, GPS, wheel encoders. • The Extras That Set You Apart • Exposure to real-world deployment of autonomous systems. • Background in optimization, control, or numerical methods for trajectory planning. • Familiarity with learning-based or hybrid planning approaches. • Contributions to open-source planning or control frameworks. • Familiarity with safety-critical autonomy and industrial robotics use cases. • This position is for our FieldAI Federal Team. This team works on projects connected to the U.S. government which requires U.S. Person eligibility. A U.S. Person as defined by 22 C.F.R §120.62 includes U.S. Citizen, U.S. National, lawful permanent residents (green card holders) refugee or asylee. • $70,000 - $300,000 a year

Benefits

• The salary range for this role is $70,000-$300,000. The actual offer for this position will be based on factors such as relevant experience, competencies, certifications, and how well the candidate meets the qualifications outlined above. Part of our compensation package also includes full benefits, equity, and generous time. • We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.