AI Medical Imaging Engineer Job Description Template

The AI medical imaging engineer develops machine learning models that analyze clinical images, typically for detection, segmentation or measurement. The technical work is demanding and the surrounding requirements more so, since clinical claims need evidence, models need validation across representative populations and the software usually falls within the regulated device definition.

Typical Duties and Responsibilities

• Develop deep learning models for clinical image analysis tasks
• Curate and annotate training data with clinical input
• Design validation studies representative of the intended use population
• Assess model performance across demographic and equipment subgroups
• Implement model inference within the product with acceptable latency
• Support regulatory submission with model documentation and evidence
• Monitor deployed model performance and detect drift
• Work with radiologists on ground truth definition and error review
• Document model development, data provenance and limitations
• Investigate failure cases and improve the model accordingly

Education

• Master’s or PhD in computer science, machine learning, biomedical engineering or a related field

Required Skills and Experience

• 3+ years applying deep learning to medical imaging
• Strong Python and a modern deep learning framework
• Understanding of medical image formats and preprocessing
• Experience designing clinically meaningful validation
• Awareness of bias and subgroup performance in clinical models
• Ability to work with clinicians on annotation and ground truth
• Understanding of regulatory expectations for AI based devices
• Careful documentation of data and model provenance

Preferred Qualifications

• Experience with a regulatory submission for an AI device
• Publications in medical imaging or machine learning