Machine Learning Engineer - Medical Imaging
Pubblicato il 09-08-2026 - trtwo in Lazio
Machine Learning Engineer - Medical Imaging
Si assicuri di leggere attentamente le informazioni relative a questa possibilità prima di inviare la sua candidatura.
Career path towardLead 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 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 xysqume 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
#J-*****-Ljbffr