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September 17, 2026
Senior MLOps / LLMOps Engineer
Senior • On-site
45,000 - 75,000 EUR/yr
Aachen, NW, Germany
Apply now
Quick Facts
- Role: Senior MLOps / LLMOps Engineer
Description
You will own end-to-end lifecycle operations for productive ML and LLM systems, covering versioning, deployment, monitoring, and continuous improvement. The role focuses on building CI/CD pipelines for AI, designing evaluation architectures (datasets, metrics, prompt evaluation), and implementing observability for drift, latency, token usage, and answer quality. You will ensure reproducibility with auditability, traceability, and controlled rollbacks in AI system landscapes.
Responsibilities
- End-to-end lifecycle: versioning, deployment, monitoring, and continuous development of ML/LLM systems in productive operation
- CI/CD for AI: implement automated training, testing, and deployment pipelines including model and prompt versioning
- Evaluation architectures: design structured test sets, golden datasets, and metrics for objective quality measurement of ML and RAG systems
- Observability: implement monitoring for model drift, data drift, latency, token consumption, and response quality
- Reproducibility: ensure auditability, traceability, and controlled rollbacks in AI system landscapes
Requirements
- Completed degree in Computer Science, Data Engineering, Software Engineering, or comparable technical field
- At least 3 years of experience operating productive ML or LLM systems in an enterprise environment
- Deep knowledge in ML/LLM quality management: model lifecycle management, drift detection, and prompt evaluation
- Proficiency with MLflow or Weights & Biases
- Experience with CI/CD toolchains such as GitLab CI or GitHub Actions
- Experience with container and cloud environments
- Structured working style with high engineering standards focused on quality, stability, and reproducibility
- Confident and precise use of AI tools and critical evaluation of results
- Good communication skills in German and English, oral and written
Benefits
- Health promotion
- Flexible work models
- Support for families
- Extensive training and further education opportunities
- Strong team spirit
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