{"slug": "robotics-autonomy-engineer-planning-and-control-federal-field-ai", "title": "Robotics Autonomy Engineer-Planning and Control - Federal — Field AI", "summary": "Field AI, a robotics company based in Irvine, California, is hiring a Robotics Autonomy Engineer for Planning and Control to develop motion planning and control algorithms for robots operating in unpredictable environments. The role requires a PhD with 2+ years of experience or equivalent, and involves designing algorithms for navigation, trajectory generation, and control across wheeled, legged, and humanoid platforms. Field AI is building risk-aware AI systems for real-world deployment, aiming to advance embodied intelligence beyond simulation.", "body_md": "# Robotics Autonomy Engineer-Planning and Control - Federal\n\n- Salary\n- Not published\n- Location\n- Irvine, CA\n- Work type\n- On-site\n- Posted\n- today\n\n[Apply on company site (opens in new tab)](https://jobs.lever.co/field-ai/ab84f5f7-8c84-4a71-835f-752bffe48de1/apply)\n\nWho are We?\n\nField AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.\n\nLearn more at https://fieldai.com.\n\nAbout the Job\n\nField AI is building the future of autonomy, from rugged terrain to real-world deployment. We are on a mission to develop intelligent, adaptable robotic systems that operate beyond simulation and thrive in unpredictable environments.\n\nAs our Robotics Autonomy Engineer – Planning and Control, you will design, implement, and deploy advanced motion planning and control algorithms that enable our robots to move with precision, robustness, and efficiency across diverse environments. You will work on navigation, trajectory generation, and motion control for robotic platforms ranging from wheeled and legged systems to complex humanoid architectures. If enabling robots to navigate challenging, dynamic environments excites you, and you want to work where your code works in the physical world - this is your role. This is Field AI.\n\nWhat You’ll Get To Do\n\n1. Develop Robust Motion Planning Algorithms\n\nDesign, develop, and refine motion and navigation planning algorithms for challenging real-world scenarios such as narrow passages, dynamic obstacles, and complex environments.\n\nDesign optimization-driven approaches for path and trajectory generation that ensure smooth, reliable, and efficient robot navigation across modalities.\n\nEnsure scalability, reusability, and adaptability of planning approaches across diverse deployment contexts.\n\n2. Advance Control and Planning Integration\n\nDevelop and tune control algorithms that ensure precise trajectory tracking and stable operation across different robotic systems.\n\nCollaborate across autonomy layers to ensure seamless coordination between perception, planning, and control for robust real-world performance.\n\n3. Validate and Test Across the Stack\n\nBuild and maintain testing pipelines from unit-level validation to full robot deployment.\n\nUtilize simulation and testing environments for algorithm evaluation, benchmarking, and regression validation.\n\nAnalyze real-world telemetry to diagnose issues, identify improvements, and enhance algorithm robustness.\n\n4. Diagnose and Improve Field Performance\n\nInvestigate and resolve issues arising from field deployments through structured data analysis and debugging.\n\nDeliver targeted improvements that address specific challenges while maintaining general-case reliability and performance.\n\nWhat You Have\n\nPhD 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.\n\nStrong understanding of motion planning, trajectory generation, and control systems.\n\nExperience developing algorithms for one or more robotic systems (wheeled, legged, wheeled-legged, humanoid).\n\nFamiliarity with motion planning libraries like OMPL, MoveIt, Nav2 stack etc\n\nSolid programming skills in C++ and Python on Linux-based systems.\n\nFamiliarity with robotics middleware such as ROS/ROS 2.\n\nExperience with robot sensors including LiDARs, stereo/depth cameras, IMUs, GPS, wheel encoders.\n\nThe Extras That Set You Apart\n\nExposure to real-world deployment of autonomous systems.\n\nBackground in optimization, control, or numerical methods for trajectory planning.\n\nFamiliarity with learning-based or hybrid planning approaches.\n\nContributions to open-source planning or control frameworks.\n\nFamiliarity with safety-critical autonomy and industrial robotics use cases.", "url": "https://wpnews.pro/news/robotics-autonomy-engineer-planning-and-control-federal-field-ai", "canonical_source": "https://frontierroles.com/jobs/field-ai-robotics-autonomy-engineer-planning-and-control-federal-5e6c41/", "published_at": "2026-09-08 00:05:47+00:00", "updated_at": "2026-09-08 03:31:19.713363+00:00", "lang": "en", "topics": ["robotics", "artificial-intelligence"], "entities": ["Field AI"], "alternates": {"html": "https://wpnews.pro/news/robotics-autonomy-engineer-planning-and-control-federal-field-ai", "markdown": "https://wpnews.pro/news/robotics-autonomy-engineer-planning-and-control-federal-field-ai.md", "text": "https://wpnews.pro/news/robotics-autonomy-engineer-planning-and-control-federal-field-ai.txt", "jsonld": "https://wpnews.pro/news/robotics-autonomy-engineer-planning-and-control-federal-field-ai.jsonld"}}