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In this role, you will collaborate with autonomy, guidance, navigation and control (GNC), flight software, and AI engineers to design, implement, and deploy computer vision algorithms thatoperateeffectively in dynamic, real-world environments. You will work across object detection, tracking, visual localization, scene understanding, sensor fusion, and perception-driven autonomy to enable robust autonomousoperationsin challenging mission scenarios.
The ideal candidate combines strong computer vision fundamentals with practical experience deploying perception systems on robotic or autonomous platforms. You will play a key role in developing vision capabilities that support navigation, obstacle avoidance, target tracking, and mission autonomy while contributing to the broader autonomy stack deployed on operationalaircraft.
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.
Education:Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, ora relatedtechnical field.
Experience:2–4years of industry experience in computer vision, robotics, machine learning, or autonomous systemsORMaster's degree with1–2years of industry experience.
Strongproficiencyin C++, Python, or Rust.
Experience with OpenCV and modern computer vision frameworks.
Experience developingperceptionsystems usingPyTorch, 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-basedperceptionalgorithms.
Familiarity with sensor fusion and state estimation techniques.
Experience with ROS/ROS2 or similar robotics middleware.
Experience developing software in Linux environments.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.