WOFÜR WIR SIE SUCHEN
* 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
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