Internship in AI & Machine Learning

ZEISS; Karlsruhe; On-site; EUR 13,000 - 20,000; Part time

Benefits offered by this job

Interdisciplinary environment

Hands-on ML projects

Full ML pipeline experience

Mentorship from experts in DL

Agile work environment

Job summary

ZEISS Innovation Hub @ KIT invites motivated students to develop AI-based solutions for real-world vision tasks, including agricultural applications. You will participate in data collection, simulation-based data generation, and model development, ending with deployment on target devices.

The role offers hands-on experience across the full ML pipeline, including vision foundation models, data preprocessing, and model quantization.

Qualifications

• Bachelor's or Master's in computer science, mathematics, physics, AI, or related fields.
• Strong Python and PyTorch programming skills.
• Solid software development fundamentals.
• Knowledge of data preprocessing for computer vision and vision foundation models.
• English or German communication skills.
• Experience with edge-device deployment and model quantization is a plus.
• Able to work independently and in a team.
• Creative, analytical, and motivated.

Responsibilities

• Develop AI-based solutions for real-world vision tasks, including agricultural applications.
• Collect data, generate simulated data, and develop models for deployment on target devices.
• Build and evaluate ML pipelines, including preprocessing and curation.
• Curate, structure, and version datasets for reproducible experiments.
• Create data preprocessing pipelines for AI/ML 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

Software development

Data preprocessing

Edge-device deployment

Model quantization

Education

Bachelor's or Master's in CS/AI/Math/Physics

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.