About Us
Daedalean is a Zürich-based startup founded by seasoned engineers dedicated to revolutionizing air travel within the next decade. We integrate computer vision, deep learning, and robotics to develop fully autonomous flying vehicles, achieving a groundbreaking "level-5" autonomy.
Your Role
In this position, you will be responsible for applying certifiable Machine Learning models in the realm of computer vision within the innovative domain of aviation.
Your Responsibilities
- Ensure our neural networks operate efficiently across diverse conditions by combining efforts on data, model design, and training.
- Guarantee performance through meticulous design and verification activities within our Machine Learning certification framework, developed in collaboration with regulatory bodies.
- Utilize transfer learning to significantly enhance the volume of training and evaluation data, particularly through simulation.
Preferred Qualifications and Experience
- Exceptional programming skills in C++ 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, ideally spanning the entire stack from model architecture to the design and implementation of evaluation pipelines.
- Proven research skills in both industrial and academic settings, with the capacity to tackle challenging problems over extended periods.
Experience in aerospace engineering or avionics is not required; we will provide you with the necessary training regarding the constraints of safety-critical systems in airworthy applications.
Benefits
- Be part of a team with experienced engineers and researchers from renowned companies and institutions.
- Engage in challenging and intriguing problems that push the boundaries of innovation.
- Participate in test flights in the breathtaking Swiss Alps.
- Enjoy a hybrid work environment.
- Access to a Learning & Development budget to attend conferences of your choice.
- Complimentary gym membership.
Apply online using the form below. Please note that only applications matching the job profile will be considered.