Autonomy SME, Lead
$112,800–$257,000 year
On-siteWashington, District of Columbia, United States
Job Summary
Design and deploy machine learning models for perception, navigation, and collaborative autonomy on unmanned systems using frameworks like Hivemind. Develop reinforcement learning algorithms and sensor fusion pipelines integrating EO, IR, LiDAR, and GPS-denied data for edge compute platforms. Lead architecture decisions, mentor engineering teams, and build simulation-based training pipelines for autonomy validation. Optimize inference latency, implement CI/CD pipelines, and conduct hardware-in-the-loop testing while adhering to DoD cybersecurity standards. Integrate AI outputs into tactical networks and support flight testing for operational demonstrations.
Required Qualifications
- 5+ years of experience in software engineering, including AI/ML systems
- Experience with Python and C++
- Experience with deep learning frameworks, such as PyTorch, TensorFlow, and ONNX
- Experience building and deploying AI models on edge hardware, such as NVIDIA Jetson, GPUs, and embedded platforms
- Experience with robotics middleware, such as ROS or ROS2
- Experience with computer vision or autonomous navigation systems
- Experience leading technical teams, architecture decisions, or autonomy-focused development efforts
- Experience integrating autonomous systems into operational, test, or simulation environments
- Ability to obtain a Secret clearance
- Bachelor's degree in a Computer Science, Robotics, Aerospace Engineering, or Electrical Engineering field
Desired Qualifications
- Experience working in military exercises and war games
- Experience with autonomy frameworks such as Hivemind, PX4, ArduPilot, NVIDIA Isaac, or ROS2
- Experience with collaborative autonomy, swarming, or multi-agent mission execution
- Ability to support flight testing and operational evaluations
- Top Secret clearance
- Master's degree ML, AI, or Solution Architecture Certification
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