About Us
Daedalean is a Zürich-based startup founded by seasoned engineers aiming to revolutionize air travel within the next decade. We merge computer vision, deep learning, and robotics to develop full “level-5” autonomy for flying vehicles.
Your Role
You will be applying first certifiable Machine Learning models in the area of computer vision within an entirely new domain—aviation.
Your Responsibilities
- Ensure that our neural networks perform robustly in all conditions by integrating efforts on data, model design, and training.
- Guarantee this performance through meticulous design and verification activities under our ML certification framework, developed in collaboration with regulators.
- Leverage transfer learning to significantly enhance the volume of training and evaluation data, particularly through simulation use.
Preferred Qualifications and Experience
- Master’s or PhD degree in computer science, physics, mathematics, or a related technical field.
- Practical experience in deep learning for computer vision, ideally covering the entire stack from model architecture to the design and implementation of evaluation pipelines.
- Demonstrated research skills in industrial and/or academic settings, with the ability to tackle challenging problems over extended periods.
- Excellent programming skills, including familiarity with a system programming language such as C++ or Rust.
Experience in aerospace engineering or avionics is not required; we will provide comprehensive training on the constraints of safety-critical systems in airworthy applications.
Benefits
- A team of experienced engineers and researchers, joining us from well-regarded companies and institutions.
- Engaging and challenging problems to solve.
- Opportunities for test flights in the stunning Swiss Alps.
- Pilot license subsidy.
- Hybrid work environment.
- Learning & Development budget: attend conferences of your choice.
- Gym membership.
Apply online using the form below. Please note that only applications matching the job profile will be considered.