Principal AI Engineer - Unmanned Autonomous Systems (Internal Use)

·       Design and integrate complex mechanical, electrical, and software components for autonomous robotic systems.

·       Develop and implement advanced algorithms for navigation, obstacle avoidance, and coordinated mission execution.

·       Create multi-modal perception systems using sensor fusion (e.g., LiDAR, cameras, IMUs) for environmental mapping and object recognition.

·       Integrate flight controllers and autopilot systems (e.g., PX4) into system architectures to ensure seamless communication and control.

·       Conduct system-wide debugging, integration testing, and performance tuning in both simulation (e.g., AirSim, Gazebo SITL with PX4) and real-world environments.

·       Develop methodologies for fault detection, redundancy, and failure recovery to enhance system reliability.

·       Optimize overall system performance and energy efficiency for extended operations under dynamic conditions.

·       Collaborate with interdisciplinary teams (AI researchers, control engineers, hardware designers) to ensure seamless system functionality.

·       Prototype, test, and iterate on novel autonomous capabilities in simulation and field environments.

Required Qualifications:

·       Master’s or PhD in Robotics, Mechanical Engineering, AI, or a closely related field.

·       3+ years of hands-on experience in autonomous systems development or equivalent R&D experience (strong research records from PhD candidates are encouraged).

·       Proficiency in C++ and Python; experience with ROS is a plus.

·       Strong background in sensor fusion, SLAM, and multi-agent coordination.

·       Demonstrated experience with flight controllers or autopilot systems (e.g., PX4) in robotic platforms is highly desirable.

Preferred Qualifications:

·       Postdoctoral research experience in robotics, autonomous systems, or related fields.

·       Experience with AI-driven decision-making and learning-based autonomy.

·       Proficiency in simulation platforms (e.g., AirSim, Gazebo SITL with PX4, CoppeliaSim) and rapid prototyping.

·       A strong publication record in robotics, AI, or autonomous systems research.