Principal Machine Learning 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.

Your role:

To technically guide the Machine Learning engineering team and help build the first certified AI avionics.

• Actively contribute to the application-level development and verification of our flagship Visual Traffic Detection system.
• Oversee our Machine Learning certification strategy.
• Maintain and grow our data processing and ML training infrastructure.
• Oversee a large codebase with Rust, Python and C++.
• Being willing to pick any task that is too urgent, complex and/or boring for someone else to take care of.
• Being able to make the most of relatively limited resources (headcount, infrastructure).

• Excellent programming skills in C++ and/or Rust.
• Master’s or PhD degree in computer science, physics, mathematics or a related technical field.
• Practical experience in deep learning for computer vision in the industry setting, ideally covering the whole stack from model architecture to the design and implementation of evaluation pipelines.
• Proven research skills in industrial and/or academic environments, including the ability to work on difficult problems over long periods of time.
• Proven experience leading projects with tight deadlines.
• Great communication skills.

Experience in aerospace engineering or avionics is not required; we will teach you everything you need to know about the constraints of safety critical systems in airworthy applications.

• 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.
• Learning & Development budget: visit conferences of your choice.
• Gym membership.