Machine Learning Engineer (m/w/d)

We build productive KI-systems (LLM, RAG, Agents) for large customers in the public sector. No prototype for the drawer, but software that runs in regular operation.

Who we are

Rockstar developers, founded 2015, offices in Stuttgart and Munich. From hundreds of projects for enterprise and mid-sized customers, we know how to build software that holds up in the long run.

We've been shifting our focus towards KI: LLM applications, RAG, Agent systems, which actually go productive at the customer's site. That's exactly what we're looking for.

About this

Our customers are IT service providers in the public sector, a regulated environment with high demands on data protection and operational safety. There, you'll build KI solutions into existing industry solutions: dialog systems, semantic search, RAG pipelines, Agents, everything in real productive operation for many users. Project language is German.

A word about remote work, because it's often the first question: Regular working hours are remote-first within the DACH region. Occasionally, you'll be on-site, and the rest of the time, you'll work from where you work best.

Your tasks

• Build LLM applications. You develop dialog-based systems and semantic search and integrate them into the industry solutions' functional applications.
• Set up and maintain RAG systems. Including knowledge base management: indexing, updating, clean storage of structured and unstructured content.
• Operation and monitoring. MLOps in productive operation: observability, structured logging, error analysis. You ensure that the systems run, not just once ran.
• Set Agents productively. From development to integration and binding to portal systems until stable delivery.
• Improve on data basis. Based on monitoring data, tests, and user feedback, you make the solutions better step by step.
• Test new things. You identify new KI application fields, test them out, and build the data pipelines from preparation to modeling to production.

You must bring

The following four points are hard requirements; each must be verifiable. If one of these is missing, we can't send you into the fray. We're that honest rather than taking up your time.

• At least 3 years of professional experience as a Machine Learning Engineer in conception, development, implementation, and optimization of scalable ML solutions.
• At least 2 years of experience in agile development teams.
• German at least on C1 level in word and writing, verifiable through a language certificate or as mother tongue.
• Completed studies in computer science, business informatics, or a comparable education, verifiable through a diploma or self-declaration.

You ideally bring

No must-have, but the more of these, the better:

• Vectors search and semantic indexing in vector databases, preferably Milvus
• Backend development with Python, preferably FastAPI
• LLM orchestration with LangChain or LangGraph
• Operating production-like KI systems: monitoring (ideally Grafana), structured logging, error analysis, deployment
• Data protection-compliant KI design, especially when handling personal data in logging and observability
• GenAI in use for many users, ideally in a multi-tenant environment
• Kubernetes, ArgoCD, Jenkins
• Experience with agile delivery structures, ideally SAFe
• Experience from projects in the public administration sector

What we offer

• Real productive projects. KI that runs at the customer's site. No innovation lab, no slides.
• Remote-first in the DACH region. Occasionally on-site, otherwise you'll work from where you work best.
• Modern KI stack. RAG, Agents, vectors search, MLOps. Current stack, no legacy baggage.
• Internal upskilling. We invest in your KI skills.
• MacBook, except the customer provides their own hardware.
• Flat hierarchies. The founders are your direct point of contact.
• A team that knows each other, even when working remotely.

Sounds like you?

If so, apply! A resume is enough; no cover letter needed. If you're available early on, that's a clear plus. We'll get in touch within a few days.

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