Then come and join our global team as Machine Learning Infrastructure and Data Engineer (f/m/d) in Magnetic Resonance Imaging (MRI).

Choose the best place for your work – Within the scope of this position, it is possible, in consultation with your manager, to work mobile (within Germany) up to an average volume of 60% of the respective working hours.

Even more flexibility? Mobile working from abroad is possible for up to 30 days a year under certain conditions and in selected countries.

Your tasks and responsibilities:

• In this role, you will be responsible for managing high-performance GPU clusters and cloud resources to support regulatory-compliant AI development in medical imaging.
• You will shape, administer and continuously maintain a machine learning compute and storage infrastructure consisting of an NVIDIA DGX cluster, cloud resources and a data management solution.
• You will manage a Kubernetes cluster for container orchestration and efficient workload distribution and collaborate closely with data scientists and engineers to optimize infrastructure components and data pipelines.
• You manage a Kubernetes cluster for container orchestration and workload distribution.
• You collaborate with data scientists and engineers to optimize infrastructure and data pipelines.
• Furthermore, you will support clinical data management.
• You will monitor system performance using tools like Prometheus and Grafana and implement security measures for IT infrastructure.
• You will manage storage servers (local and cloud) and ensure seamless connectivity to compute clusters.

To find out more about the specific business, have a look at Magnetic Resonance Imaging  

Your qualifications and experience:

• You hold a university degree in Computer Science, Mathematics, Engineering or a comparable field.
• You have several years of professional experience in the administration of machine learning infrastructure, preferably in the context of medical imaging or healthcare.
• You have sound knowledge of Linux system administration, including scripting and automation, and practical experience with cloud platforms, ideally Microsoft Azure, as well as hybrid cloud environments.
• In addition, you are familiar with networking, storage management and security concepts.
• You possess solid programming skills in Python, Bash and PowerShell for automation purposes.
• Experience in GPU cluster management, in particular with NVIDIA Base Command Manager, as well as experience in Kubernetes-based container orchestration, is considered an asset.
• Knowledge of clinical data management and medical image processing is a plus.
• Familiarity with machine learning frameworks such as TensorFlow and PyTorch, as well as experience with monitoring and logging tools such as Prometheus and Grafana, is advantageous.
• Relevant certifications (e.g. CKA or RHCE) are also welcome.

Your attributes and skills:

• Since the development teams of the Application Release Train are distributed internationally across three locations, you communicate confidently in English.
• You are proactively committed to delivering high-quality solutions and contribute constructively to cross-functional development teams.
• You present your ideas and results clearly and convincingly and value close collaboration and teamwork.
• A strong sense of responsibility and the highest quality standards in product development are a matter of course for you