Autonomy & UAS Lead Engineer

Booz Allen Hamilton; Washington; On-site; USD 113,000 - 257,000; Full time

Job summary

Booz Allen Hamilton is seeking an Autonomy SME, Lead to design, deploy ML models powering autonomous unmanned systems. You will guide autonomy architecture, mentor teams, and support integration into military platforms, applying edge AI, computer vision, and reinforcement learning.

Expect collaboration with government stakeholders and ongoing field demonstrations. Lead architecture decisions, develop capable autonomy pipelines, and ensure deployment readiness across edge compute platforms and

Qualifications

• Bachelor's degree in Computer Science, Robotics, Aerospace Engineering, or Electrical Engineering.
• 5+ years of software engineering experience including AI/ML systems.
• Experience with Python and C++.
• Experience with PyTorch, TensorFlow and ONNX.
• Experience deploying AI models on edge hardware (NVIDIA Jetson, GPUs).
• Experience with ROS or ROS2.

Responsibilities

• Design and train ML models for perception, detection, tracking, and classification.
• Develop RL and autonomy algorithms for navigation and mission execution.
• Implement sensor fusion of EO, IR, LiDAR, GPS-denied data.
• Optimize AI models for edge compute platforms (GPU, TPU, embedded).
• Lead autonomy architecture decisions and mentor engineering teams.
• Collaborate with government stakeholders and engineers to define autonomy requirements.

Skills

Python

C++

AI/ML systems

Deep learning

Edge AI

Team leadership

Security clearance

Education

Bachelor's degree

Tools

PyTorch

TensorFlow

ONNX

ROS/ROS2

NVIDIA Jetson

Job description

Booz Allen Hamilton is seeking an Autonomy SME, Lead to design, deploy ML models powering autonomous unmanned systems. You will guide autonomy architecture, mentor teams, and support integration into military platforms, applying edge AI, computer vision, and reinforcement learning.

Expect collaboration with government stakeholders and ongoing field demonstrations. Lead architecture decisions, develop capable autonomy pipelines, and ensure deployment readiness across edge compute platforms and