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!
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.
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
