AI & Machine Learning Internship

Motivation of the Work  

Turning today’s research into tomorrow’s applications, together. At ZEISS, we focus on user-centric innovation to transform ideas into cutting-edge solutions. The ZEISS Innovation Hub @ KIT brings together students, researchers, and industry professionals to advance AI, computer vision, and machine learning in application-oriented projects. 

Your Role

We are looking for highly motivated students to develop AI-based solutions for real-world vision tasks, including agricultural solutions, from data collection, simulation-based data generation, and model development to deployment on target devices. This internship provides hands-on experience across the full ML pipeline, including vision foundation models, data preprocessing and curation, quantization-aware training, edge-device deployment, and performance evaluation.

• Develop an efficient and reproducible workflow for application-oriented machine learning solutions. 

• Be involved in sample preparation and data acquisition in the laboratory for full data ownership 

• Implement quantitative metrics to assess and optimize data preprocessing quality and guide relabeling efforts 

• Curate, structure, and version datasets for reproducible experiments 

• Build data preprocessing pipelines for AI and machine learning workflows 

• Generate and evaluate simulation-based or synthetic data 

• Run hyperparameter and model studies in a traceable environment.  

• Automate embedded-device tests and optimize accuracy and speed. 

We Offer

• A dynamic and interdisciplinary environment 

• Hands-on experience with real-world image, sensor, and simulation-based data, foundation models, model quantization, and edge deployment 

• Learn how to set up a full machine learning pipeline 

• Close mentorship from experts in deep learning 

• An agile work environment 

Your Profile

• Enrolled in a Bachelor’s or Master’s program in computer science, mathematics, physics, AI, or related fields

• Strong programming skills in Python and PyTorch

• Solid understanding of software development principles

• Fundamental knowledge of data preprocessing steps for computer vision and vision foundation models

• Familiarity with AI/ML concepts (e.g., supervised learning, deep learning architectures) is a plus

• Experience with edge-device deployment and model quantization is a plus

• Creative, pragmatic, and self-motivated with strong analytical skills

• Capable of working independently as well as in a team-oriented environment 

• Excellent communication skills in English or German

• Passion for innovation, enthusiasm for new technologies, and motivation to contribute to interdisciplinary projects

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

Your ZEISS Recruiting Team:

Selina Safradin