Daedalean18mo ago

Machine Learning Engineer

ZürichFull-Timemid

Data ScienceMachine Learning EngineerDataData & AI

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Quick Summary

Overview

About us: Daedalean AG is the artificial intelligence (AI) and autonomy hub of Destinus Group,

Technical Tools

Data ScienceMachine Learning EngineerDataData & AI

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:

Applying first certifiable Machine Learning models in the area of computer vision in an entirely new domain - aviation.

Ensure that our neural networks perform strongly in all conditions, by combining work on data, model design, and training.

Ensure that this performance can be guaranteed, through careful design and verification activities, under our ML certification framework developed in collaboration with regulators.

Leverage transfer learning to massively increase the amount of training and evaluation data available, in particular through the use of simulation.

Excellent programming skills in C++ or Rust.

Master’s or PhD degree in computer science, physics, mathematics or a related technical field.

At least 5 years of 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.

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.