Machine Learning Engineer - Medical Imaging

trtwo; Roma; On-site; EUR 60,000 - 80,000; Full time

Job summary

trtwo is seeking a Machine Learning Engineer specialized in medical imaging to develop and deploy deep learning models for radiology and pathology applications with rapid, reliable performance.

You will work with a multidisciplinary team of doctors, data scientists and engineers to bring AI from research to clinical practice, build data pipelines for DICOM preprocessing, and ensure MDR/AI Act compliance. Equity may be offered.

Qualifications

• MSc or PhD in Computer Science, Biomedical Engineering or related field.
• 3+ years with deep learning frameworks (PyTorch preferred).
• Strong experience with CNNs, U‑Net, Vision Transformers for medical imaging.
• Experience with medical imaging data (DICOM, NIfTI).
• Python proficiency and familiarity with MLOps tools.

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.

Skills

Deep learning for medical imaging

CNNs/U‑Net/ViTs

Python

MLOps

Medical imaging analysis

Education

MSc or PhD in Computer Science or Biomedical Engineering

Tools

PyTorch

TensorFlow

Job description

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