Senior MLOps Engineer (m/f/d)

Introduction

You take AI models from prototype to production—scalable, robust, and ready for the real world.

Tasks

• You implement and maintain ML pipelines for data ingestion, training and deployment as well as CI/CD processes for models.
• You containerize and package AI applications for hybrid cloud and on-premise environments.
• You deploy models on Kubernetes, Azure and edge target systems and optimize them in terms of latency, accuracy and energy efficiency.
• You implement monitoring, logging, drift detection and A/B testing for production models.
• You ensure reproducibility and experiment tracking throughout the entire model lifecycle, including versioning and metadata management.
• You work closely with AI/ML engineers to make prototypes production-ready.

Qualifications

• You bring several years of hands-on experience in MLOps or a comparable role, particularly in deploying models on cloud and on-premise infrastructures.
• You have solid Python skills as well as experience with containerization (Docker/Podman), orchestration (Kubernetes) and CI/CD/GitOps workflows (GitLab, Helm charts).
• You have experience with ML lifecycle tools such as experiment tracking, model versioning and monitoring, as well as with deployment considerations for edge and low-power environments.
• You stand out through a strong automation and reliability mindset as well as strong troubleshooting skills at both the infrastructure and model level.
• You are characterized by teamwork skills, communication skills, willingness to learn, analytical thinking and presentation skills.
• Very good German skills and very good English skills (written and spoken) round off your profile.

Contact and further information

We welcome your application! Submissions are preferred online via the application portal. For questions, our chatbot Paul and the recruiting team are available at any time.

Rohde & Schwarz promotes equal opportunities and welcomes applications from people with and without disabilities. We offer an inclusive work environment where all individuals can develop their skills and talents regardless of gender, nationality, ethnic and social background, religion, worldview, age, sexual orientation, identity, and other characteristics.