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Machine Learning Engineer - Full Time

Munich, Germany or remote | engineering
Starting date:
January 2022 or later
2.1 - Developing contributor

Your role

You work on the brain of our intelligent products. By leveraging your algorithmic skills you create automatic classification models for our imaging data.
Working closely with the innovation team, you code ML models for complex 3D data, improve them throughout their lifecycle, and develop simulations for our digital twin. By leveraging your analytical mindset and problem-solving skills, you own a cornerstone of our AI-powered imaging technology.

Your experiences and skills

We hope to hear from you if any of these apply:
  • You know how to process and analyze 3D imaging data.
  • You proficiently train models to generate insights within large data sets.
  • You identify yourself with one or more of these attributes: member of an underrepresented group, non-linear career path, otherwise unique profile.
We look for this in all our team members:
  • You are a changemaker: you are passionate and purpose-driven.
  • You are a teamplayer: you seek to connect with and build upon the skills and knowledge of others to achieve the best possible outcome for everyone.
  • You are a builder: you turn big dreams into reality.
  • You identify yourself with our core values:
    • We own every challenge: we enjoy complexity and thrive under uncertainty.
    • We strive for better: we seize any opportunity for growth and challenge the status quo. We are constantly learning and improving.
    • We imagine new frontiers: we think beyond ‘doable’ and ‘reasonable’. We design a sustainable and healthy future together.

What we offer

You join an ambitious team working on breakthrough technology.
We offer you a plain playing field to explore and design. During your time with Orbem, we support you in discovering your strengths and defining a vision for your professional future. We hope to teach you some things, but more importantly we also want to learn from you. Join us.

Speak with us

Kai Riemenschneider