Computer Vision Engineer

About us:

Daedalean AG is the artificial intelligence (AI) and autonomy hub of Destinus Group, a rapidly growing European defense and aerospace company developing the next generation of autonomous drones, effectors, and flight systems. Based in Zurich, the 100+ team develops safety-critical AI for aviation at the intersection of world-class research and real hardware. Its expertise spans computer vision, deep learning, and onboard reasoning – systems that can perceive the world, understand it, and make decisions in real time.

To improve the algorithms and models of Daedalean's existing range of products in order to make them more accurate and reliable, as well as to develop and implement new algorithms, extending the systems' functional range and making them employable in a wider range of applications and environments.

• Develop and implement computer vision algorithms and deep learning models for localization and mapping, object detection and tracking, classification, general image processing, and related functions - as well as analyze, extend, and improve the existing code base and models.
• Collaborate with other engineering teams (such as flight testing, hardware, sensor fusion) to integrate computer vision solutions into prototypes and products.
• Test and evaluate the performance, robustness, and reliability of computer vision systems in diverse conditions, to ensure accuracy, reliability, and efficiency. This may involve both simulated and real-world environments.

• Excellent programming skills in C++; experience with Rust is a plus.
• Experience with computer vision systems, ideally including both classical techniques and deep learning methods.
• Hands‑on experience with tools like OpenCV, PyTorch, Tensor Flow.
• Master’s or PhD degree in Computer Vision, Computer Science, Robotics, Electrical Engineering, or a related technical field.

• A team of experienced engineers and researchers, who joined us from most recognized companies and institutions.
• Difficult and interesting problems to solve.
• Hybrid work setting.
• Gym membership.