Senior MLOps Engineer (m/f/d)

RxREVU, Inc.; Dresden; Vor Ort; EUR 70.000 - 95.000; Vollzeit

Zusammenfassung

Rohde & Schwarz is seeking an experienced MLOps engineer to take AI models from prototype to production-ready, scalable systems. You will build and maintain end-to-end ML pipelines, containerize applications, and deploy across hybrid cloud, on-premise, and edge targets.

You will optimize latency and energy efficiency on Kubernetes and cloud platforms, implement monitoring, drift detection, A/B testing, and ensure reproducibility with experiment tracking and metadata management.

Qualifikationen

• Hands-on MLOps experience deploying models on cloud and on-premise infrastructure.
• Strong Python skills and experience with containerization, orchestration, and CI/CD workflows.
• Experience with ML lifecycle tools for experiment tracking, model versioning, and monitoring.
• Strong automation, reliability, and troubleshooting skills at infrastructure and model level.
• Excellent teamwork, communication, learning mindset, analytical thinking and presentation skills.
• Very good German and English skills (written and spoken).

Aufgaben

• Implement and maintain ML pipelines for data ingestion, training and deployment, plus CI/CD for models.
• Containerize and package AI applications for hybrid cloud and on‑premise environments.
• Deploy models on Kubernetes, cloud platforms and edge target systems, optimizing latency, accuracy and energy efficiency.
• Implement monitoring, logging, drift detection and A/B testing for production models.
• Ensure reproducibility and experiment tracking across the model lifecycle, including versioning and metadata management.
• Work closely with AI/ML engineers to make prototypes production-ready.

Kenntnisse

MLOps experience

Python

Containerization

Kubernetes

CI/CD/GitOps

Experiment tracking

Edge deployment

Automation & reliability

Teamwork & communication

German & English fluency

Tools

Docker/Podman

Kubernetes

GitLab

Helm charts

Jobbeschreibung

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.

Exciting insights into Rohde & Schwarz

Our colleagues provide insider information about:

• Daily adventures and challenges
• Our passionate team
• The technologies behind the innovative projects and solutions

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.

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.