Staff Consultant – Medical Imaging AI/ML

Role Overview

• 4–8 years in AI/ML, Data Science, or Medical Imaging; 3+ years in medical imaging AI.
• Develop, fine-tune, validate, and benchmark AI models for tumor/lesion segmentation and risk prediction.
• Work closely with radiologists, clinicians, data scientists, and technical teams.
• Remote, with willingness to travel to client locations.

Key Responsibilities

• Fine-tune pre-trained models using transfer learning and hyperparameter optimization.
• Develop segmentation and predictive models using PyTorch, MONAI, nnU-Net.
• Evaluate segmentation using Dice, IoU, Hausdorff Distance, Sensitivity, Specificity, Precision, Recall.
• Build risk prediction models using imaging + clinical data.
• Develop scalable and reproducible medical imaging inference pipelines.
• Perform validation, benchmarking, cross-validation, and external testing.
• Test model generalizability across institutions, scanners, protocols, and patient populations.
• Identify bias, performance degradation, and recommend improvements.
• Prepare technical documentation, validation reports, and stakeholder presentations.

Must-Have Skills

• Python, PyTorch, MONAI, nnU-Net
• NumPy, Pandas, Scikit-learn, Git
• Deep learning, transfer learning, fine-tuning, hyperparameter tuning
• Medical imaging: CT, MRI, PET, Digital Pathology
• DICOM and tumor segmentation workflows
• Model validation, benchmarking, statistical analysis
• Risk prediction and predictive analytics
• Generalizability/external validation
• Knowledge of radiomics, imaging biomarkers, and Explainable AI