Internship in AI & Machine Learning (f/m/x)

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