Machine Learning Systems Engineer (UAS) - 1685

We are seeking a highly skilled engineer to spearhead the development of unmanned navigation and control technologies, with emphasis on flight controller integration, autonomous navigation, and AI-driven edge processing. This role involves developing and configuring flight control systems, integrating sensors, optimizing embedded software, and deploying AI models on embedded platforms. The ideal candidate will collaborate across hardware, software, and AI teams to advance the boundaries of autonomous aerial systems.

Core Responsibilities

• Assist with configuring and integrating flight controllers running PX4 or ArduPilot, including Cube-based hardware, with various UAV platforms
• Support firmware flashing, flight controller parameter configuration, PID tuning, motor mapping, ESC calibration, and sensor integration and calibration under the guidance of experienced engineers
• Develop, modify, and test software using C++ and/or Python to support flight control, sensor processing, and communication with Jetson-based AI/vision systems
• Assist with integrating ROS and MAVLink interfaces for communication between flight controllers, companion computers, and ground control systems
• Support computer vision and AI-based perception activities, including object tracking and simultaneous localization and mapping (SLAM), using tools such as OpenCV, TensorFlow, PyTorch, and DeepStream
• Assist with deploying and evaluating AI models on NVIDIA Jetson platforms, learning techniques for efficient real-time inference
• Support networking, telemetry, and video streaming integration for UAV command, control, and monitoring
• Participate in laboratory, simulation, and field testing, including test setup, data collection, troubleshooting, and documentation, following established safety procedures
• Collaborate with hardware, software, and AI team members to resolve integration issues and document technical results

Requirements

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related field
• 0–2 years of relevant experience in UAS, robotics, embedded software, controls, or related engineering activities; relevant internships, academic projects, research, and personal projects will be considered
• Foundational programming skills in C++ and/or Python
• Basic understanding of control systems, sensors, and embedded computing through coursework or practical experience
• Familiarity with one or more relevant technologies, such as PX4, ArduPilot, MAVLink, ROS, or UAV flight controllers
• Ability to troubleshoot technical problems, follow test procedures, and clearly document results
• Interest in autonomous navigation, computer vision, and AI processing on embedded platforms
• Ability to work effectively as a member of a multidisciplinary team, communicate technical information, and learn new tools and technologies
• U.S. citizen with the ability to obtain and maintain a DoD security clearance
• May require moderate physical effort, including standing, sitting, use of hands while performing duties, and carrying or lifting up to 50 pounds
• Working environment is indoor, moderately quiet, reasonably clean, well-lighted and well-ventilated; moderate physical hazards may exist

Preferred Qualifications

• 2+ years of relevant hands-on experience with flight controller integration, UAV software or hardware development, robotics, or embedded systems
• Master’s degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related field
• Hands-on experience through internships, capstone projects, research, robotics competitions, or personal UAV projects
• Familiarity with Linux, particularly Ubuntu
• Experience configuring PX4 or ArduPilot, using MAVLink or ROS, or working with QGroundControl or Mission Planner
• Exposure to PID tuning, sensor calibration, autonomous navigation, or navigation in GPS-denied environments
• Familiarity with NVIDIA Jetson platforms, OpenCV, TensorFlow, PyTorch, DeepStream, and/or CUDA
• Exposure to real-time embedded systems, wireless communications, telemetry, or video streaming
• Familiarity with UAV test and validation procedures and hardware debugging tools such as oscilloscopes, logic analyzers, or protocol analyzers
• Active DoD security clearance, preferably Top Secret