Machine Learning Engineer - Autonomy
$110,000–$165,000 year
On-siteSterling, Virginia, United States
Job Summary
Develop and deploy machine learning and autonomy capabilities for uncrewed aircraft, focusing on perception, tracking, sensor fusion, and mission-level decision making. Integrate autonomy software with autopilots, companion computers, and flight-control functions while maintaining clear interfaces. Build production-quality C++ and Python software optimized for NVIDIA GPU and embedded edge-compute platforms. Utilize simulation, SIL, HIL, and automated test environments to evaluate behavior and reduce risk prior to flight. Support aircraft integration, ground testing, and flight test by analyzing logs and driving performance improvements. Collaborate with Machine Learning Engineers, Platform Engineers, and cross-functional teams to advance capabilities from development through real-world deployment.
Required Qualifications
- BA/BS degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or a related technical field, or equivalent practical experience
- 2-5 years of experience developing and deploying machine learning or autonomy software on robotic, autonomous, or UAS platforms
- Strong C++ and Python development skills, including Linux-based development and modern machine learning frameworks
- Working knowledge of perception, sensor integration, autonomous decision making or planning, and real-time system integration
- Professional working proficiency in English (spoken and written)
- Ability to work effectively in a standard office, engineering laboratory, aircraft integration, hangar, and outdoor flight-test environment
- Ability to stand, walk, bend, kneel, reach, and work around aircraft, ground-support equipment, test equipment, and computing hardware for extended periods as required
- Ability to lift, carry, and position equipment and components weighing up to 25 pounds, with or without reasonable accommodation
- Ability to safely work in outdoor environments and varying weather conditions during ground and flight-test activities
- Ability to work around aircraft systems, electrical equipment, rotating equipment, batteries, and other laboratory/flight-test hazards while following applicable safety procedures and PPE requirements
- Ability to visually inspect equipment, read computer displays, instrumentation, schematics, logs, and test data, with or without reasonable accommodation
- Ability to work flexible hours, including early mornings, evenings, or occasional weekends, when required to support aircraft integration, ground testing, or flight-test operations
- Ability and willingness to travel to company facilities, customer sites, and/or designated flight-test locations as required by the position
Desired Qualifications
- Direct experience with UAS autonomy, aircraft integration, or flight test
- Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and vehicle interfaces
- Aerospace or defense experience and eligibility to obtain a DoD Secret clearance
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