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Field AI

Industry:
Robotics
Location:
Job Type:
Artificial Intelligence
Robotics Autonomy Engineer-Planning and Control
Job Description:
Field 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.
Job Responsibilities:
  • 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 – Planning and Control, you’ll 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’ll 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 hits the ground (literally) — this is your role. This is Field AI.
    • Job Requirements:
  • 1. 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.
    •  
  • 2. 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.
    •  
  • 3. 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.
    •  
  • 4. 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.
    • Bonus Qualifications:
  • Master’s degree or higher in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field (PhD a plus).
  • Strong understanding of motion planning, trajectory generation, and control systems.
  • Experience developing algorithms for one or more robotic systems (wheeled, legged, wheeled-legged, humanoid).
  • 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
    • Apply on Field AI Website
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