Machine Learning Engineer - Medical Imaging

ph3Machine Learning Engineer - Medical Imaging /h3 pCareer path toward bLead ML Engineer or Head of AI within 2-3 years /b /p h3Industry Sectors /h3 pHealthcare Medical, Information Technology, Research Development /p h3Technologies you'll work with /h3 ppowered by Job Nautilus /p h3Salary /h3 p60,000 - 80,000 EUR/year + equity /p h3Job Description /h3 pAn 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. /p pYou will work with a multidisciplinary team of doctors, data scientists and engineers to bring AI from research to clinical practice. /p h3Responsibilities /h3 ul liDevelop and train deep learning models for medical image classification and segmentation /li liBuild data pipelines for DICOM image preprocessing and augmentation /li liCollaborate with radiologists for model validation and clinical testing /li liDeploy models via containerised inference services with sub-second latency /li liStay current with latest research in medical AI and computer vision /li liEnsure compliance with MDR and AI Act requirements for medical devices /li /ul h3Must-have Requirements /h3 ul liMSc or PhD in Computer Science, Biomedical Engineering or related field /li li3+ years experience with deep learning frameworks (PyTorch preferred) /li liStrong experience with CNNs, U-Net, Vision Transformers for image analysis /li liExperience with medical imaging data (DICOM, NIfTI) /li liPython proficiency and familiarity with MLOps tools /li /ul h3Nice-to-have Requirements /h3 ul liPublications in medical imaging or computer vision conferences /li liExperience with FDA/CE marking processes for AI medical devices /li liKnowledge of federated learning approaches /li /ul h3Personal Requirements /h3 ul liPassion for applying AI to improve healthcare outcomes /li liRigorous scientific approach with attention to reproducibility /li liAbility to communicate complex technical concepts to non-technical stakeholders /li liEthical mindset regarding AI in healthcare /li /ul /p #J-18808-Ljbffr