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.
• 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 in

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

Attributes aligned with Core Values