Computer Vision Engineer – Autonomy & Perception

Responsibilities

Perception & Computer Vision: Design and develop perception systems for autonomous aerial platforms operating in GPS-denied and contested environments; implement object detection, classification, segmentation, and tracking algorithms using RGB, thermal, and multimodal sensor data; develop visual perception pipelines for obstacle detection, collision avoidance, and situational awareness; build scene understanding capabilities to support autonomous navigation and mission execution; evaluate and integrate state-of-the-art computer vision and AI techniques into operational systems. 

Visual Navigation & Localization: Develop visual-inertial odometry, localization, and mapping algorithms; implement vision-based navigation solutions for degraded and GPS-denied environments; support SLAM and feature-based localization systems; design robust estimation methods that fuse camera, IMU, GPS, lidar, and radar data; improve navigation performance through sensor fusion and environmental awareness. 

Machine Learning & AI: Develop, train, and deploy deep learning models for onboard perception; create data processing, labeling, augmentation, and evaluation pipelines; optimize neural networks for real-time inference on embedded computing platforms; analyze model performance and improve robustness across operational conditions; support deployment of perception models on edge AI hardware. 

Camera Systems & Sensor Integration: Integrate and evaluate diverse imaging systems including RGB, stereo, fisheye, thermal, and event-based cameras; develop camera calibration workflows and sensor characterization procedures; support multi-camera synchronization and calibration efforts; improve image quality, calibration accuracy, and perception system reliability; collaborate with hardware teams to evaluate and integrate emerging sensor technologies. 

Testing & Validation: Develop simulation and testing frameworks for perception algorithms; support software-in-the-loop, hardware-in-the-loop, and flight testing activities; analyze flight data to identify performance gaps and improve perception robustness; establish metrics and validation procedures for autonomous perception systems; document system performance and support field deployments. 

Qualifications

• Education: Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related technical field. 

• Experience: 2–4 years of industry experience in computer vision, robotics, machine learning, or autonomous systems OR Master's degree with 1–2 years of industry experience. 

• Strong proficiency in C++, Python, or Rust. 

• Experience with OpenCV and modern computer vision frameworks. 

• Experience developing perception systems using PyTorch, TensorFlow, or similar machine learning frameworks. 

• Strong understanding of image processing, geometric vision, and camera systems. 

• Experience with object detection, tracking, segmentation, and machine learning-based perception algorithms. 

• Familiarity with sensor fusion and state estimation techniques. 

• Experience with ROS/ROS2 or similar robotics middleware. 

• Experience developing software in Linux environments. 

Preferred Qualifications

• Master's or PhD in Computer Vision, Robotics, Machine Learning, Computer Science, or a related field. 
• Experience with autonomous aircraft, UAVs, robotics, or aerospace systems
• Experience with visual SLAM, visual-inertial odometry, or localization systems. 
• Knowledge of camera calibration, multi-camera systems, and geometric computer vision. 
• Experience integrating lidar, radar, thermal cameras, and inertial sensors into perception systems. 
• Experience deploying AI models on embedded platforms such as NVIDIA Jetson or similar edge computing hardware. 
• Familiarity with simulation environments such as Gazebo, Isaac Sim, AirSim, or equivalent. 
• Experience optimizing perception systems for real-time performance and resource-constrained platforms. 
• Contributions to open-source robotics, autonomy, or computer vision projects.
• Familiarity with defense industry standards and security clearance processes. 

Attributes aligned with Core Values

Safety Above All: Demonstrates a proactive safety mindset by embedding safety into daily work, identifying and mitigating risks, encouraging open dialogue about safety concerns, and continuously improving practices and protocols.
Customer Focus: Puts customers at the center of every action by understanding their challenges, delivering meaningful value, and supporting their success.
Work Better Together: Seeks and values diverse perspectives, builds cross-functional relationships, and fosters trust through empathetic, fact-based communication and commitment to shared decisions.
Be the Pilot: Drives results with clarity and purpose by focusing on what matters most, adapting to change, taking initiative, and owning outcomes.
Embrace the Unknown: Navigates ambiguity with resilience and bold thinking, challenges the status quo, and combines innovative ideas with practical approaches to overcome obstacles and drive progress.
Respect for People: Fosters a high-performance culture grounded in respect, professionalism, and support by balancing high expectations with a healthy, collaborative environment and being a trusted, dependable teammate.