Senior MLOps Engineer (m/f/d)

Rohde & Schwarz USA, Inc.; Dresden; Vor Ort; EUR 60.000 - 75.000; Vollzeit

Zusammenfassung

Rohde & Schwarz USA, Inc. in Dresden is seeking an ML/AI engineer to take models from prototype to production. You will build end-to-end ML pipelines, containerize applications, and deploy across Kubernetes, Azure and edge devices. The role emphasizes latency, accuracy and energy efficiency, with strong focus on monitoring and experiment tracking.

You will collaborate with AI/ML engineers to ensure prototypes are production-ready and scalable across hybrid cloud and on-prem environments.

Qualifikationen

• Experience building ML pipelines from ingestion to deployment.
• Familiar with containerization and hybrid cloud environments.
• Knowledge of model monitoring and A/B testing.
• Strong collaboration with AI/ML engineers.

Aufgaben

• 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.

Kenntnisse

ML pipelines

Kubernetes

CI/CD

Containerization

Tools

Kubernetes

Azure

CI/CD

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.