Internship Multimodal AI for Video Understanding (m/f/x)

Welcome to ZEISS – a company that combines innovation and responsibility! Our corporate functions are diverse and make a decisive contribution to the strategic orientation and sustainable success of ZEISS.

Your role

At ZEISS Corporate Research & Technology, we are offering student positions (internship and/or master’s thesis) in the area of multimodal AI and video understanding.

• You will work on research problems at the intersection of vision, language, and structured data, with a focus on developing models that can understand complex real-world scenarios such as surgical workflows

• The goal is to move beyond frame-level analysis towards holistic, temporally consistent representations that integrate multiple sources of information

• Your tasks Contribute to research on multimodal and video-based machine learning methods, develop and evaluate models for holistic video understanding (e.g. video-language models, temporal reasoning, multimodal fusion)

• Work with real-world datasets and problem settings from ZEISS applications, implement and analyze state-of-the-art approaches and extend them in a research-driven setting

Your profile

• Enrolled in a Master’s or PhD program in Computer Science, Machine Learning, or a related field in Germany

• Strong fundamentals in machine learning and deep learning

• Experience with Python and common ML frameworks (e.g. PyTorch)

• Interest in research and ability to work independently on open-ended problems

• Experience with video analysis, multimodal learning, or foundation models is a plus

What we offer

• Opportunity to work on cutting-edge research with real-world impact

• Close collaboration with research teams at ZEISS Corporate Research and Technology

• Possibility to transition from internship to master’s thesis based on performance

• Access to challenging datasets and modern ML infrastructure

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