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

Carl Zeiss SMT; Karlsruhe; On-site; EUR 8,900 - 13,000; Full time

Benefits offered by this job

Dynamic environment

Hands-on with ML pipeline

Mentorship from experts

Agile work environment

Job summary

Carl Zeiss SMT at the Innovation Hub @ KIT invites motivated students to develop AI-based solutions for real-world vision tasks, from data collection to deployment on edge devices. You will work on agricultural applications, data generation, model development, and performance evaluation across the ML pipeline.

Join a dynamic, interdisciplinary team with mentorship from deep learning experts, gaining hands-on experience with vision foundation models, data preprocessing, quantization-aware

Qualifications

• Currently enrolled in a Bachelor's or Master's program in CS, math, physics, AI, or related fields.
• Strong Python and PyTorch programming skills.
• Solid understanding of software development principles.
• Experience with data preprocessing for computer vision and vision foundation models.
• Familiarity with AI/ML concepts; edge-device deployment and model quantization is a plus.
• Excellent communication in English or German.

Responsibilities

• 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.

Skills

Python

PyTorch

Data preprocessing

Edge deployment

Model quantization

English/German communication

Git

Linux

Education

Bachelor's or Master's student

Tools

Git

NumPy

Linux

Job description

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