Architekten der Digitalen Zukunft
Machine Learning Engineer – m/f/d
Location
Germany
Posted
4 days ago
Salary
0
Seniority
Senior
Job Description
Machine Learning Engineer – m/f/d
RockstarDevelopers GmbH
• Build LLM-based applications. • Develop conversational systems and semantic search and integrate them into the domain-specific applications of the industry solution. • Set up and maintain RAG (Retrieval-Augmented Generation) systems. • Including knowledge-base management: indexing, updates, and clean, source-separated storage of structured and unstructured content. • Operation and monitoring. • MLOps in production: observability, structured logging, and error analysis. • Ensure systems run reliably in production, not just that they worked once. • Deploy agents into production. • From development through integration and connection to portal systems to stable delivery. • Improve solutions based on data. • Use monitoring data, tests, and user feedback to iteratively improve solutions. • Experiment with new approaches. • Identify new AI use cases, prototype them, and build data pipelines from preprocessing and model development to production.
Job Requirements
- At least 3 years of professional experience as a Machine Learning Engineer in the design, development, implementation, and optimization of scalable ML solutions.
- At least 2 years of experience working in agile development teams.
- German language proficiency at least at C1 level (spoken and written), demonstrable by a language certificate or as a native speaker.
- Completed degree in Computer Science, Business Informatics, or a comparable qualification, verifiable by certificate or self-declaration.
- Vector search and semantic indexing in vector databases, ideally Milvus.
- Backend development with Python, preferably FastAPI.
- LLM orchestration with LangChain or LangGraph.
- Operation of production-grade AI systems: monitoring (ideally Grafana), structured logging, error analysis, deployment.
- Privacy-compliant AI 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.
Benefits
- Real production projects.
- AI that goes into operation at customer sites.
- Not an innovation lab — real deployments, not just slide decks.
- Remote-first within the DACH region.
- Occasional on-site presence; otherwise work from wherever you are most productive.
- Modern AI stack.
- RAG, agents, vector search, MLOps.
- Current stack, no legacy baggage.
- Internal upskilling.
- We invest in your AI skills.
- MacBook provided, unless the client supplies their own hardware.
- Flat hierarchies.
- Founders are your direct contacts.
- A team that knows each other, even when working remotely.
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