Machine Learning Engineer - Autonomy
Core
Develops and deploys machine learning and autonomy capabilities for hydrogen-powered uncrewed aircraft systems (UAS), focusing on perception, tracking, sensor fusion, and mission-level decision making.
Role type
Machine Learning Engineer (Autonomy)
Builds
Autonomous flight software and perception systems for UAS
Domain
Aerospace / Robotics / Autonomous Systems
Deliverable
production ML models
Required skills
C++, Python, Machine Learning frameworks, Sensor fusion, Perception (object detection/tracking), Real-time system integration, Simulation (SIL/HIL), Linux development
Preferred skills
NVIDIA edge compute (CUDA/TensorRT), ROS 2, MAVLink, UAS/Flight test experience, DoD Secret clearance eligibility
Technologies
C++, Python, Linux, NVIDIA GPU, CUDA, TensorRT, ROS 2, MAVLink
Responsibilities
Develop and integrate perception capabilities including object detection, classification, tracking, and sensor fusion; Develop mission-level autonomous behaviors using state machines, behavior trees, and planners; Integrate autonomy software with autopilots, mission computers, and sensors; Develop production-quality C++ and Python software optimized for embedded edge-compute platforms; Support aircraft integration, ground test, and flight test of autonomy capabilities.
Seniority
Mid-level, hands-on IC