Your mission

• Develop and optimize SLAM algorithms for real-time UAV mapping and autonomous navigation
• Implement sensor fusion techniques combining Lidar, Radar, EO/IR, IMU, and GPS data
• Enhance localization accuracy in GPS-denied environments using vision-based SLAM (ORB-SLAM, VINS-Mono)
• Design and deploy probabilistic mapping techniques (e.g., Kalman Filters, Particle Filters, Graph-SLAM)
• Improve loop closure detection and drift correction for long-term UAV autonomy
• Optimize SLAM models for low-latency execution on embedded and edge AI platforms
• Integrate SLAM into swarm coordination frameworks for multi-UAV mapping

Your profile

• 3+ years experience in SLAM, sensor fusion, and real-time navigation
• Strong expertise in computer vision-based SLAM (ORB-SLAM, VINS, DSO, LSD-SLAM)
• Proficiency in C++, Python, or Rust for high-performance robotics applications
• Experience with ROS2, DDS, and real-time UAV navigation frameworks
• Knowledge of probabilistic filtering techniques (EKF, UKF, Particle Filters)
• Familiarity with embedded and edge AI hardware (Jetson, FPGA, Edge TPU)

• Experience in multi-agent SLAM for UAV swarm mapping
• Background in deep learning-based visual odometry and SLAM
• Knowledge of adversarial environments and SLAM resilience against sensor spoofing

Why us?

Join us to shape the future of AI-driven defense!

Do you feel that you fit the description, but don't think you fulfill all the criteria 100%? Apply to us anyway.   
We look forward to receiving your detailed application via our online form.  

The world is changing. Exponential technologies are enabling new types of security threats. We are committed to staying ahead by building nimble, scalable, and cost-effective defences. We are looking for passionate developers who are eager to create exceptional products, safeguard our freedom, and strengthen the resilience of democracies.