Staff Engineer, Perception (R5611)

Hybrid London, United Kingdom
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit  www.shield.ai . Follow Shield AI on  LinkedIn ,  X ,  Instagram , and  YouTube .  

Shield AI’s mission is to protect service members and civilians with intelligent systems. We are seeking a Senior or Staff Robotics Perception Engineer to develop and deploy advanced perception and navigation capabilities for autonomous aircraft operating in complex and GNSS-denied environments.

This role requires deep expertise in visual-inertial odometry (VIO), visual SLAM, vision-based navigation, state estimation, and camera–IMU sensor fusion. You will take algorithms from early-stage prototypes through embedded implementation, field testing, and flight validation on operational autonomous platforms.

This is not a general AI/ML or object-detection role. We are looking for an engineer whose core expertise lies at the intersection of robotics perception, VIO/SLAM, state estimation, camera and inertial sensing, and real-time embedded deployment.

What you'll do:

  • Design, develop, and deploy VIO, visual SLAM, visual localization, and vision-based navigation capabilities for autonomous aircraft.
  • Develop robust state-estimation and sensor-fusion solutions using cameras, IMUs, and other onboard sensors.
  • Build geometric computer-vision components, including feature tracking, optical flow, pose estimation, triangulation, and visual localization.
  • Develop geo-localization and map-matching capabilities using satellite, aerial, or orthophoto imagery.
  • Integrate perception and navigation algorithms with flight-control and autonomy systems.
  • Implement and optimize algorithms in C++ for real-time operation on embedded Linux platforms.
  • Develop and maintain real-time camera and video-processing pipelines using technologies such as GStreamer and V4L2.
  • Optimize workloads for NVIDIA Jetson, Orin, or comparable embedded-compute platforms, including CUDA and TensorRT where appropriate.

Required qualifications:

  • Significant hands-on experience developing robotics perception or navigation systems.
  • Strong expertise in VIO, visual SLAM, vision-based navigation, or GNSS-denied localization.
  • Deep understanding of camera–IMU sensor fusion, state estimation, calibration, and time synchronization.
  • Strong knowledge of geometric computer vision, including feature tracking, optical flow, pose estimation, triangulation, and visual localization.
  • Experience deploying perception or navigation capabilities on UAS/UAVs or other autonomous robotic platforms.
  • Strong C++ development skills and experience working in Linux environments.

Preferred qualifications:

  • Experience with NVIDIA Jetson, Orin, or similar embedded-compute platforms.
  • Experience optimizing perception workloads using CUDA, TensorRT, or comparable acceleration technologies.
  • Hands-on experience with GStreamer, V4L2, camera pipelines, and real-time video processing.
  • Experience deploying containerized software to embedded platforms using Docker.
  • Experience with vision-based navigation, geo-localization, or map matching using satellite, aerial, or orthophoto imagery.
  • Familiarity with frameworks and libraries such as OpenVINS, VINS-Fusion, ORB-SLAM3, GTSAM, Ceres Solver, OpenCV, or Kalibr.
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Our international teammates receive a comprehensive total rewards package aligned to your country office location. For full details on compensation and benefits, please consult your talent acquisition partner.

Source: the employer's careers page. Last checked 2026-09-30. Posted 2026-08-27.

Applications happen on Shield AI's own site. View role and apply

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