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Senior Machine Learning Engineer

Job

  • Level
    Senior
  • Job Field
    Software, Data
  • Employment Type
    Full Time
  • Contract Type
    Temporary employment
  • Location
    Frankfurt
  • Working Model
    Onsite
  • Job Summary

    In this role, you will develop production-ready AI models for radiology, oversee end-to-end ML pipelines, and optimize deep learning models for medical image analysis using diverse data sources.

    Job Technologies

    Your role in the team

    • We are looking for you as a Senior Machine Learning Engineer for the Machine Learning working group at the University Medical Center Frankfurt am Main.
    • Develop production-ready AI models for radiology using data from the RACOON network - Germany's largest radiology research initiative with 38 university hospitals.
    • You take full responsibility for end-to-end ML pipelines with the freedom to prototype solutions that can evolve into competitive AI solutions.
    • Development, training, validation, and deployment of deep learning models for medical image analysis (primarily CT and MRI-based).
    • Full pipeline responsibility: From DICOM data acquisition to containerized deployment.
    • Rapid Prototyping: Fast transition from clinical problem to working prototype.
    • Performance optimization for accuracy, inference speed, and computational efficiency.
    • Setup and maintenance of training environments: configuration of GPU servers, compute resource management.
    • Development of reusable ML infrastructure: modular pipelines, data loaders, training frameworks.
    • Deployment systems: Implementation of inference services, APIs, and integration with PACS systems.
    • DICOM/FHIR data processing: robust parsers, converters, and quality assurance systems.
    • Data Versioning and Lineage: Tracking systems for reproducible experiments.
    • Privacy-Preserving Workflows: Data processing compliant with GDPR and German health data protection law.
    • Multi-institutional data integration of RACOON's 38 partner institutions.
    • Publication in top venues for medical AI (RSNA, ECR, MICCAI, Medical Image Analysis).
    • Contribution to collaborative research projects (RACOON, COMPARE, ENRICH).
    • Opportunity for promotion by individual agreement.

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    Our expectations of you

    Education

    • Master's degree in (Medical) Informatics, Physics, Mathematics, Data Science, or a comparable field.

    Qualifications

    • Expert-level Python programming: PyTorch or TensorFlow, NumPy, scikit-learn, pandas.
    • Linux expertise: proficient in shell scripting, SSH, file systems, process management.
    • Version Control & Collaboration: Git workflows, code review practices, CI/CD fundamentals.
    • Self-employed: You identify problems, propose solutions, and implement them.
    • Pragmatic: They balance research quality with the shipping of functioning systems.
    • Very good knowledge of German as well as good knowledge of English.
    • A valid proof of measles immunity / measles vaccination is required due to legal regulations.

    Experience

    • Proven expertise in machine learning: demonstrable experience in training neural networks.
    • Deep learning experience: You have trained CNNs, Vision Transformers, or other architectures from scratch.

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    Benefits

    Health, Fitness & Fun

    Work-Life-Integration

    Topics that you deal with on the job

    Job Locations

    • Location Frankfurt

      Hessen

      Germany

    This is your employer

    Universitätsklinikum Frankfurt

    Universitätsklinikum Frankfurt

    Das Universitätsklinikum Frankfurt besteht seit 1914 und unsere rund 6.500 Beschäftigte bringen sich mit ihrem Können und Wissen an den 32 Fachkliniken, klinisch theoretischen Instituten und in den Dezernaten ein.

    Description

  • Company Type
    Established Company
  • Working Model
    Onsite
  • Industry
    Healthcare, Social Sector, Science, Research
  • Logo Universitätsklinikum Frankfurt

    Senior Machine Learning Engineer

    Location
    Frankfurt
    Working Model
    Onsite
    Diversity
    Open for all genders

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