Robotics Autonomy Engineer-Planning and Control - Federal

Design, develop, and refine motion and navigation planning algorithms for challenging real-world scenarios such as narrow passages, dynamic obstacles, and complex environments.

Design optimization-driven approaches for path and trajectory generation that ensure smooth, reliable, and efficient robot navigation across modalities.

Ensure scalability, reusability, and adaptability of planning approaches across diverse deployment contexts.

Develop and tune control algorithms that ensure precise trajectory tracking and stable operation across different robotic systems.

Collaborate across autonomy layers to ensure seamless coordination between perception, planning, and control for robust real-world performance.

Build and maintain testing pipelines from unit-level validation to full robot deployment.

Utilize simulation and testing environments for algorithm evaluation, benchmarking, and regression validation.

Analyze real-world telemetry to diagnose issues, identify improvements, and enhance algorithm robustness.

Investigate and resolve issues arising from field deployments through structured data analysis and debugging.

Deliver targeted improvements that address specific challenges while maintaining general-case reliability and performance.

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.

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.

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.

You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field , winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.

To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.

We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates.

Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!

We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.