Working Student Machine Learning Engineering

As a working student (m/f/d) in the Analytics & AI department, you support the Machine Learning Engineering team in developing intelligent assistants, e.g. generative AI-based chatbots or agents. You help develop, test and put AI-supported solutions into practice.

• Support in designing, implementing and further developing generative AI applications for assistant/chatbot scenarios (e.g. help work out requirements, develop prototypes and step by step drive improvements based on results and feedback)
• Work on the LLM/RAG environment: preparing and structuring knowledge sources and supporting workflows around chunking, metadata enrichment and maintenance of retrieval/index structures (e.g. embeddings)
• Help with data, inference and prompting pipelines: planning and running tests/validations in close coordination, analyzing typical error patterns (e.g. unsuitable content or missing sources) and deriving practical optimization steps

• First practical experience or solid theoretical foundations in machine learning / natural language processing, plus interest in generative AI (e.g. LLMs) and typical RAG basics (e.g. retrieval, embeddings)
• Good basic Python skills and an understanding of data/text processing workflows (e.g. cleaning, structuring, chunking as a concept, handling text formats)
• Basic SQL knowledge (e.g. to query/understand data); alternatively/additionally experience with simple data pipelines or databases
• Interest in data pipelines & quality: willingness to prepare content/knowledge sources in a structured way and help with tests/reviews (e.g. source coverage, data quality, traceability of results)
• Ideally first exposure to cloud environments or tools (e.g. AWS or Azure) or the motivation to get up to speed quickly
• Very good German skills, spoken and written, for coordination, documentation and quality assurance
• Application with a current proof of enrollment