The DLR Institute of Software Technology sees software as a catalyst for research and innovation. The institute's staff, currently numbering around 200, make a significant contribution to advancements in the fields of aviation, space, energy, transportation, and security through the development of state-of-the-art software solutions and innovative research.
Our areas of competence include reliable and safety-critical software systems, artificial intelligence, high-performance computing and quantum computing, human-system interaction and visualisation, software and systems engineering as well as digital platforms and digital twins.
What to expect
The Intelligent and Distributed Systems department researches methods to make complex technical processes and systems – from software development to automated workflows and AI-assisted analysis – traceable, automatable, and interactively experimentally accessible.
The Sustainable Software Engineering Group investigates how scientists and engineers develop software - and how they can be supported efficiently and effectively in doing so.
In this context, an AI-supported assistance system is to be prototypically developed and evaluated as part of a thesis. The aim is to explore and test recent approaches for this task in practice, such as Large Language Models (LLMs), agent-based systems, and retrieval-augmented generation (RAG).
Your tasks
* selection and integration of suitable open source LLM models
* use of Ollama (or similar tools) as an interface to local open-source LLMs
* integration of dynamic knowledge sources (e.g. DLR Software Engineering Guidelines or GitLab repositories)
* development of a simple agent workflow with e.g. Langchain, CrewAI or LlamaIndex
* design and execution of tests
Your profile
* Student of computer science (e.g. with a focus on software engineering or artificial intelligence), data science or similar.
* good knowledge of Python
* practical experience in software development
* basic understanding of concepts such as LLMs or API-based integration
* willingness to systematically familiarize yourself with new technologies
We look forward to getting to know you!
If you have any questions about this position (Vacancy-ID 2491) please contact:
Norman Müller
Tel.: +49 2203 601 1221
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