Machine Learning Engineer
Pubblicato il 25-10-2026 - 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
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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