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Machine Learning Engineer - Medical Imaging - trtwo

Pubblicato il 19-09-2026 - trtwo in Roma

Machine Learning Engineer - Medical Imaging Career path toward

Lead ML Engineer or Head of AI within 2-3 years

Industry Sectors Healthcare & Medical, Information Technology, Research & Development

Technologies you'll work with powered by Job Nautilus

Salary 60,000 - 80,000 EUR/year + equity

Job Description An innovative company in the digital health sector is building the next generation of AI-assisted diagnostic tools and is looking for a Machine Learning Engineer specialising in medical imaging. You will develop and deploy deep learning models for radiology and pathology applications.

You will work with a multidisciplinary team of doctors, data scientists and engineers to bring AI from research to clinical practice.

Responsibilities

Develop and train deep learning models for medical image classification and segmentation

Build data pipelines for DICOM image preprocessing and augmentation

Collaborate with radiologists for model validation and clinical testing

Deploy models via containerised inference services with sub-second latency





Stay current with latest research in medical AI and computer vision

Ensure compliance with MDR and AI Act requirements for medical devices

Must-have Requirements

MSc or PhD in Computer Science, Biomedical Engineering or related field

3+ years experience with deep learning frameworks (PyTorch preferred)

Strong experience with CNNs, U-Net, Vision Transformers for image analysis

Experience with medical imaging data (DICOM, NIfTI)

Python proficiency and familiarity with MLOps tools

Nice-to-have Requirements

Publications in medical imaging or computer vision conferences

Experience with FDA/CE marking processes for AI medical devices

Knowledge of federated learning approaches

Personal Requirements

Passion for applying AI to improve healthcare outcomes

Rigorous scientific approach with attention to reproducibility

Ability to communicate complex technical concepts to non-technical stakeholders

Ethical mindset regarding AI in healthcare

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