Field AI is transforming how robots interact with the real world by building risk‑aware, reliable, and field‑ready AI systems. We are building autonomous robotic systems that operate beyond simulation and thrive in unpredictable environments.
Responsibilities
Develop Robust Motion Planning Algorithms
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.
Advance Control and Planning Integration
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.
Validate and Test Across the Stack
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.
Diagnose and Improve Field Performance
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.
Qualifications
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.
Compensation
The salary range for this role is $70,000–$300,000, with the actual offer based on relevant experience, competencies, certifications, and fit. The compensation package includes full benefits, equity, and generous time off.
Equal Opportunity
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.
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