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Machine Learning Ops Engineer

Job in Zürich, 8058, Zurich, Kanton Zürich, Switzerland
Listing for: StudySmarter
Full Time position
Listed on 2025-12-09
Job specializations:
  • Software Development
    AI Engineer, Software Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 CHF Yearly CHF 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Location: Zürich

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

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
  • Proven track record of coding in C++ and/or Rust (Python experience is a plus)
  • Strong affinity to working with large amounts of data, preferably video/images
  • A good understanding of neural network experimentation, life cycle management and familiarity with associated tooling, such as Weights & Balance, Clear

    ML, Determined

    AI, 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.

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