Varied and challenging activities around medical image data, data-centric machine learning and AI-based software development, Planning, design and implementation of data pipelines for medical image data, e.g. DICOM-based workflows, Development and maintenance of processes for data ingestion, structuring and traceability, Establishment and continuous improvement of dataset governance, including data quality checking, dataset versioning, documentation, Feasibility analyses of problems regarding artificial intelligence and machine learning and the development of suitable solution strategies, Management and quality assurance of annotations, labels and ground truth data used for medical machine learning model development and validation, Support in the selection and integration of suitable tools, frameworks and technologies to improve our ML development and deployment processes according to regulatory compliance and requirements, Further development and optimization of our products/projects, Analysis and solving of complex development tasks in teamwork, Independent study of state of the art knowledge