Principal Machine Learning Engineer (Zürich, CH)

Nur für registrierte Mitglieder
Zürich
CHF 90’000 - 150’000
Jobbeschreibung

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


Your tasks:
  • 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).
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 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.
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.