Computer Vision Engineer – Autonomy & Perception

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.