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: As a ML company we produce and utilize large amounts of aerial video data that we need to store, process and make useful for our teams globally. You will be a part of the ML team designing, implementing and maintaining tools and infrastructure to support our ML development environment. These have to be efficient, scalable, reliable and adhere to very specific requirements dictated by our certification efforts whilst maintaining the necessary flexibility for the ML development. At Daedalean, we support both on-premise as well as cloud-based compute clusters. The work spans building web APIs, Kubernetes workflows, databases, storage and in-house tools written in Rust, C++, Python or Golang, as well as deploying and maintaining 3rd party software tools. You will collaborate with our ML Development, Data Management and Data Annotation teams, making sure they have everything they need to work smoothly. With the support of these teams you will take ownership of capabilities such as flight test recording processing, annotation tooling pipelines, neural network optimization algorithms, inference platforms and configuration management and inventory. Requirements:

You get things done and have:

Proven track record of coding in C++ and/or Rust (Python experience is a plus)

Strong affinity to working with large amounts data, preferably video/images

A good understanding of neural network experimentation, life cycle management and familiarity with associated tooling, such as Weights & Biases, ClearML, DeterminedAI, Ray, or similar.

Experience with cloud platforms such as AWS, Azure or GCP and the ML tools and the services they provide

Familiarity with containerization and orchestration tools such as Argo, Kubernetes, Docker, etc.

Familiarity and/or interest with web technologies such as web APIs, databases, storage systems, etc.

Benefits:

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.

Gym membership.

Machine Learning Ops Engineer