Machine Learning Engineer / MLOps Engineer (m/w/d)

Responsibilities

Our client, a confidential IT services organization in the public sector, is building production-grade AI systems—LLM applications, RAG pipelines, and agent-based solutions—that run at scale for end users. We are representing them in the search for a Machine Learning Engineer / MLOps Engineer to join their team in Stuttgart.

You will develop and operate ML pipelines in a highly regulated environment with strict data protection and operational security requirements. Your work will integrate AI capabilities into existing enterprise solutions: conversational interfaces, semantic search, retrieval-augmented generation, and intelligent agents—all deployed in production.

Day-to-day, you will:

• Develop and maintain production ML and data pipelines
• Automate data preparation and model training workflows
• Build and operate model serving infrastructure, including monitoring and alerting
• Integrate ML models into domain-specific applications
• Monitor deployed models and detect model drift
• Evolve the technical stack and DevOps/MLOps processes

Work is conducted remote-first within the DACH region, with occasional on-site presence. Project language is German.

What We're Looking For

Must-have requirements (each must be demonstrable):

• At least 3 years of professional experience in CI/CD development
• At least 3 years of professional experience in Python development
• At least 3 years of hands-on experience with Kubernetes and Docker
• At least 3 years of professional experience as a Machine Learning Engineer
• At least 3 years working in agile development teams
• German proficiency at C1 level or higher (verifiable via certificate or native fluency), both written and spoken

Preferred qualifications (the more, the better):

• DevOps or Kubernetes certification
• Experience with Prometheus and Grafana
• Software design and architecture background
• Kubeflow or OpenShift AI experience
• Practical experience operating ML models in production environments
• Jenkins and ArgoCD familiarity
• Experience in the social insurance sector
• SAFe framework knowledge

How We Work With You

Get A Job.ai is managing this search on behalf of our client. When you apply through our platform, one of our recruiters will conduct an initial screening. If there's a strong match, we will submit your profile to the client for consideration. Please do not contact the client directly—all communication flows through our talent team to ensure a structured process.

A CV is sufficient; no cover letter is required. Early availability is a clear advantage. We aim to respond within a few days of receiving your application.

Pay

Compensation will be discussed during the screening process and is commensurate with experience.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applications from candidates of all backgrounds and work to ensure fair access to opportunities.