Internship in Computer Vision / Calibration Pipelines
This job is at Carl Zeiss AG. You apply to them, not to GoAusbildung.
Start Date
On request
Sector
Optics and Technology
Salary
Competitive salary
Listing data as of November 3, 2026
About this Apprenticeship
We are seeking passionate and talented students who are eager to shape next-generation products at ZEISS. Integrated into a team of scientists and research engineers, you will work on research projects in computer vision and photogrammetry. These projects can range from custom camera calibration and simulation of camera characteristics in digital twins to object detection and depth estimation algorithms.
Requirements
- You are interested in technology and motivated to work on challenging tasks
- You are enrolled in a bachelor’s or master's degree in computer science or electrical engineering specializing in computer vision, machine learning or similar
- You have a strong computer science background with very good coding skills in Python (C++ is a plus)
- You have initial experience with computer vision, ideally camera calibration, photogrammetry, PyTorch, and OpenCV
- You understand camera models, projection geometry, coordinate systems, and basic 3D geometry.
- You are willing to collaborate and work in interdisciplinary teams
- Good communication skills in English and/or German
- You are willing to learn and explore with a high degree of initiative and creativity
What Carl Zeiss AG offers
- An opportunity to build the foundation for next-generation products
- The option to write a master thesis following an internship or working student position
- Hands-on work on intrinsic, extrinsic, and multi-camera calibration for ZEISS use cases
- The possibility of continuing employment as a working student for up to 2 years
- A unique opportunity to choose the topics that interest you most within an exciting project
- A modern working environment enabling hybrid work by offering remote workdays
- An opportunity to join a growing company with many career opportunities
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