MLOps Engineer (m/f/d)

• Deploy and operate machine learning models in standardized and scalable production environments
• Implement robust traffic handling and autoscaling mechanisms to ensure reliable and efficient model serving
• Design and manage advanced deployment strategies that reduce risk during model releases and updates
• Optimize inference performance by improving hardware utilization and minimizing latency for production workloads
• Package and release machine learning models in fully containerized and version-controlled environments
• Ensure reproducibility and integrity of model artifacts across development, testing, and production systems
• Establish comprehensive monitoring for inference performance, data quality, and model behavior in production
• Support governance and compliance by maintaining traceable release artifacts, validation results, and audit-ready documentation

• Successfully completed studies in computer science, machine learning, artificial intelligence, software engineering, or a comparable qualification.
• Several years of professional experience in machine learning operations, platform engineering, or DevOps environments supporting machine learning systems.
• Strong experience deploying and operating machine learning models in production environments.
• Solid knowledge of containerized workloads and orchestration platforms for scalable model deployment.
• Experience working with model versioning systems and managing machine learning artifacts across environments.
• Practical experience optimizing machine learning models for efficient inference and hardware utilization.
• Structured and analytical approach to solving complex operational challenges in machine learning systems.
• Strong collaboration and communication skills when working with engineering, data science, and platform teams.

An unserem Standort in Bremen bieten wir Ihnen:

• Betriebliche Altersvorsorge
• Aktienkaufprogramm
• 30 Urlaubstage
• Zugang zu den Corporate Benefits
• Deutschlandticket
• Umzugsunterstützung
• VIVA Familienservice
• Individuelle und vielfältige externe sowie interne Weiterentwicklungsmöglichkeiten u.a. in der Rheinmetall Academy
• Professioneller Einarbeitungsprozess begleitet durch ein digitales Onboarding

Zuständige/r Ansprechpartner/in: Özge Demirkaya

Für Fragen zu Ihrer Bewerbung, nutzen Sie bitte das Kontaktformular.