Principal Machine Learning Engineer

Zürich
Flight Software, Computer Vision and AI /
Full-Time /
Hybrid
About us:
Daedalean is a Zürich-based startup founded by experienced engineers who want to completely revolutionize air travel within the next decade. We combine computer vision, deep learning, and robotics to develop full “level-5” autonomy for flying vehicles.

Your role:
To guide the Machine Learning engineering team and help build the first certified AI avionics.

Your tasks:

    • Lead the application-level development and verification of our flagship Visual Traffic Detection system.
    • Manage a team of 15 machine learning engineers, researchers, and software engineers.
    • 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).

Preferred Qualifications and Experience:

    • 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, 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.

Benefits:

    • A team of experienced engineers and researchers, who joined us from most recognized companies and institutions.
    • Difficult and interesting problems to solve. 
    • Pilot license subsidy.
    • Hybrid work setting.
    • Learning & Development budget: visit conferences of your choice.
    • Gym membership.