Machine Learning Infrastructure and Data Engineer (f/m/d) in Magnetic Resonance Imaging (MRI)
Siemens
Machine Learning Infrastructure and Data Engineer (f/m/d) in Magnetic Resonance Imaging (MRI)
Job Description
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
- 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
Locations
- Erlangen, Bayern, Germany
Salary
Estimated Salary Rangemedium confidence
85,000 - 150,000 EUR / yearly
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Linux system administrationintermediate
- scripting/automation (Python, Bash, PowerShell)intermediate
- cloud platforms (Azure, hybrid)intermediate
- Kubernetes cluster managementintermediate
- networking/storage/securityintermediate
- GPU cluster managementintermediate
- monitoring (Prometheus, Grafana)intermediate
- data pipeline optimizationintermediate
Required Qualifications
- university degree in Computer Science, Mathematics, Engineering or comparable (experience)
- several years experience in ML infrastructure (medical imaging/healthcare preferred) (experience)
Responsibilities
- manage GPU clusters/cloud resources for AI development
- administer ML compute/storage infrastructure (NVIDIA DGX, cloud, data management)
- manage Kubernetes for orchestration
- collaborate with data scientists/engineers
- support clinical data management
- monitor performance/implement security
- manage storage/connectivity
Benefits
- general: mobile working up to 60% (Germany)
- general: mobile abroad up to 30 days/year
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