Machine Learning Engineer (m / f / d)

About Us

We’re DASS-X, a 100% BASF subsidiary working at the intersection of the automotive and chemical industries. We’re looking for a Machine Learning Engineer to join our team and work on real AI systems used in production environments.

We’re a culturally diverse team, English is our working language, and we value thoughtful collaboration, curiosity, and building things that actually work.

Your tasks

You’ll work as part of a team designing and building AI agents that run in real systems — not demos or research prototypes. The work spans the full lifecycle of these systems : data handling, model and agent design, orchestration, testing, deployment, and operation.

You’ll collaborate closely with other engineers and ML practitioners. This is a team environment where problems are discussed openly, ideas are shared, and solutions are built together. You’ll have space to experiment, but also responsibility for turning ideas into robust, maintainable systems.

Your profile

There’s no rigid checklist. If you’re comfortable with Python and interested in building applied machine learning and agent-based systems, that’s a solid foundation. What matters most is curiosity, a willingness to dig into complex problems, and the ability to work well with others.

It’s helpful if you’re interested in how large language models behave inside agent setups — how prompting choices influence outcomes, how tool calls are triggered and handled, and how routing or decision logic shapes system behavior.

Experience that’s useful here

• Agent-based systems (LangGraph)
• Vector stores and retrieval systems (e.g. Cosmos DB)
• Working with foundation models and platforms such as Azure OpenAI, Gemini / Vertex AI
• Git and collaborative development workflows
• CI / CD pipelines and production deployments
• Cloud platforms, particularly Azure

Familiarity with concepts such as agent-to-agent communication (A2A) and the Model Context Protocol (MCP) is considered an advantage.

Why us?

Interested?

If you’ve worked on AI-related projects — professionally, at university, or on your own — feel free to share them. A GitHub repository is ideal, and a ZIP file works as well. Seeing how you approach problems is more important than perfectly polished material.

About us

Data Space Solutions GmbH is committed to developing and providing digital applications that enable circular business models, fostering sustainable economic practices. We focus on enhancing data sovereignty and interoperability in line with EU regulations, specifically targeting the value chains in the automotive and chemical industries. By leveraging trusted digital ecosystems like Catena-X, we aim to drive innovation, sustainability, and efficiency within these critical sectors.