Internship Machine Learning

zeissgroup· Carl Zeiss Microscopy GmbH
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📍 MünchenFull time

About this role

ZEISS Microscopy - Innovation down to the smallest detail  

ZEISS Research Microscopy Solutions is a world leader in the manufacture of microscopy systems for the visualization of the tiniest structures and particles in the fields of research and science. Our light, electron and X-ray microscopes as well as software solutions that utilize AI technology enable groundbreaking discoveries in life science, materials and industrial research as well as for education and clinical practice. Renowned scientists rely on ZEISS microscopes for their research, including Robert Koch, who discovered the tuberculosis pathogen around 1900.  

Become part of our team and shape the microscopy systems of tomorrow!  

Your Role

  • You will play a crucial role in bringing new ML and CV functionality to our new revolutionary digital microscopy online platform at ZEISS

  • Together with our team of software developers and machine learning engineers you will work on improving our automated machine learning and computer vision toolset

  • You will have the possibility to improve your knowledge in areas such as automated ML pipelines, scalable ML infrastructure or our framework for training computer vision algorithms

As the leading microscopy company, we have an unlimited number of use cases for ML and CV. Datasets ranging from neuron and other cell biology images to microscopic images acquired in industrial quality labs provide us with exciting new challenges every day.

Your Profile

  • Currently enrolled in Computer Science, Data Science, Software Engineering, STEM, or a related field

  • Finding pleasure in developing production-ready software in Python, demonstrated by a portfolio of projects

  • Active user of version control (git)

  • Good understanding of the principles of modern Deep Learning and Computer Vision algorithms

  • Proven track record of contributing maintainable code to team projects or open-source projects

  • Deep curiosity and willingness to dive into new subject areas

  • Self-motivated personality, independent working style and collaborative mindset

  • Fluent in English or German

Sounds exciting? Then become part of #teamZEISS and help us shape the future! Please provide your complete application documents (CV, transcript of records).

Your ZEISS Recruiting Team:

Ines Kloda

Frequently Asked Questions

Is the salary disclosed for the Internship Machine Learning position at zeissgroup?
The salary for this Internship Machine Learning role at zeissgroup is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Internship Machine Learning position at zeissgroup located?
This Internship Machine Learning role at zeissgroup is based in München. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Internship Machine Learning role at zeissgroup full-time or part-time?
This is listed as a Full time position. It is posted as a Internship Machine Learning role in the Carl Zeiss Microscopy GmbH department at zeissgroup.
Which team or department does the Internship Machine Learning at zeissgroup belong to?
This Internship Machine Learning position is part of the Carl Zeiss Microscopy GmbH department at zeissgroup. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Internship Machine Learning position at zeissgroup?
Click the "Apply Now" button on this page. You will be redirected to zeissgroup's official application portal hosted on workday where you can submit your application directly.
When was the Internship Machine Learning job at zeissgroup posted?
This Internship Machine Learning position at zeissgroup was posted on Aug 6, 2026. Apply as soon as possible — early applications are often reviewed first.
Internship Machine Learning
zeissgroup
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You'll be redirected to zeissgroup's official application page on Workday.