Computer Vision Engineer

About the role

Imagine pushing the boundaries of what machines can perceive and decide, refining the intelligence behind autonomous flight systems that operate in the real world. You'll work directly improves the accuracy, reliability, and adaptability of cutting‑edge AI products, while also opening the door to entirely new capabilities and applications. You will evolve existing algorithms and models, and design new ones that allow our systems to perform in increasingly complex and demanding environments.

At Destinus, we are shaping the future of defense through high‑speed, autonomous flight technologies. We develop next‑generation unmanned aerial systems that deliver greater speed, precision, and efficiency, supporting governments and defense organizations in mission‑critical operations worldwide.

Daedalean AG, the AI and autonomy hub of the Destinus Group, plays a key role in this vision. Developing safety‑critical AI systems at the intersection of advanced research and real‑world aviation. Enabling machines to perceive, understand, and make decisions in real time. Together, we combine aerospace engineering and artificial intelligence to build the next generation of autonomous flight systems, driving innovation where it matters most.

• 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.

You thrive in complex, high‑stakes environments where precision matters, driven by curiosity to make systems smarter and more reliable. You experiment, iterate, and solve without waiting for direction, balancing deep technical thinking with real‑world impact. Ownership comes naturally, collaboration is seamless, and there is a constant drive to push for excellence.