Your mission

• Develop and deploy multi-sensor fusion algorithms for target detection, tracking, and classification.
• Apply Bayesian filters (e.g., Kalman, EKF, UKF, Particle Filters) and Monte Carlo methods for robust state estimation.
• Implement nonlinear and convex optimization techniques to refine estimates in real-time systems.
• Work with teams on real-world object tracking: fusing detections across time and modalities.
• Collaborate closely with hardware and perception engineers (camera, LiDAR, radar, acoustic sensors) to ensure cross-sensor calibration and alignment.
• Test your algorithms in field trials with real-world conditions — not just in simulation

Your profile

• Multi-Modal Sensor Fusion – Experience fusing data from camera, LiDAR, radar, acoustic, or thermal sensors
• Bayesian Estimation – Strong knowledge of Kalman Filters (EKF, UKF), Particle Filters, Monte Carlo methods
• Object Tracking – Hands-on experience with multi-object tracking, probabilistic data association, and filter tuning
• Nonlinear / Convex Optimization – Practical experience applying optimization in real-time systems
• Statistical Modeling – Deep understanding of Gaussian processes, uncertainty modeling, and signal processing
• Real-Time Systems – Experience deploying algorithms on real-time embedded or autonomous platforms
• Domain Expertise – Background in autonomous driving, robotics, aerospace, or defense systems

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.