Principal AI Engineer - Unmanned Autonomous Systems, AI.DA STC

Unmanned Autonomous Systems Engineer

Job Overview

We seek a talented Unmanned Autonomous Systems Engineer to lead the development of multi-robot systems that operate autonomously in complex, dynamic environments. In this role, you will combine deep technical expertise in mechanical and electrical engineering with innovative algorithm development to create robotic systems capable of executing sophisticated missions and responding to their environment in real-time. You will collaborate with distinguished professors and industry experts, pushing the boundaries of multi-agent robotics—from sensor fusion to system-wide robustness enhancements.

Key Responsibilities:

• 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.