AI Working Student (Werkstudent) (Project-Based )

Details zur Stelle

We're looking for a driven and tech-savvy Working Student (Werkstudent) to join our AI team. You’ll support the development and maintenance of generative AI models, help build intelligent agent scripts, work on computer vision tasks, and get your hands dirty with data scraping and analysis.
If you're excited about large language models, multimodal AI, and computer vision—and want hands-on experience working with real-world applications—this role is for you!

Key Responsibilities:

Test AI models and agents from a user perspective to evaluate performance, edge cases, and output quality
Write and iterate on agent prompts, scripts, and logic
Support computer vision workflows: data collection, preprocessing, model evaluation
Clean, analyze, and visualize datasets to uncover insights or improve models and define the data quality requirements
Collaborate with researchers and engineers on experimentation and documentation
You present the results and recommendations for action to the stakeholders.
Assist in developing new use cases using artificial intelligence or machine learning

Qualifications:

Must-have:

Strong Python skills and familiarity with AI/ML libraries (e.g., PyTorch, HuggingFace, OpenCV, LangChain)
Basic understanding of LLMs, GenAI concepts, and CV tasks
Clear communication and documentation habits
Good programming skills in Python
An insatiable appetite for learning and a knack for problem-solving.
Enrolled Master's student in the field of data science, (business) computer science, mathematics or a comparable course of study.

Nice-to-have:

Portfolio of machine learning, data analysis or visualization projects (e.g. on Kaggle, Github)
You are experienced in dealing with databases.
Familiarity with prompt engineering or autonomous agent frameworks (e.g., Auto-GPT, LangGraph)
Hands-on experience training or fine-tuning models
Knowledge of cloud platforms (AWS, GCP) or MLOps tools
Scrape data from the web and structured sources for training and analysis

What We Offer:

Design your working hours to fit your semester schedule.
You have the chance to contribute and implement your own ideas.
Work in a motivated, diverse team and achieve great things together.
Last but not least, you will gain a deep insight into the day-to-day business of the department.

Send us your CV, GitHub (if available), and a short note on why you’re interested in [email protected]