Junior AI Engineer

About the role

Daignostix builds clinical AI for CT, MR, X-ray and ultrasound, with algorithms spanning neuro and stroke, pulmonary embolism, aortic pathology, urology, spine and rib fracture, solid-organ trauma and paediatric chest. As a Junior AI Engineer, you will own scoped model workstreams (data, training, evaluation and error analysis) under the guidance of senior AI engineers, and support the move of validated models into production.

What you'll do

• Model development. Train, fine-tune and evaluate CNN- and transformer-based models for classification, detection and segmentation
• Data pipelines. Build and maintain DICOM pipelines for ingestion, de-identification, series selection, pre-processing, augmentation
• Evaluation and error analysis. Report clinical metrics (sensitivity, specificity, PPV/NPV, ROC-AUC/PR-AUC, per-case and per-lesion)
• Production support. Contribute to packaging validated models as tested inference services (Python, Docker, FastAPI)

What you need

• 2–4 yrs of experience
• Python
• Machine learning
• Deep learning
• Scikit-learn
• TensorFlow
• Computer vision
• B.Tech or B.E. or M.Tech or M.Sc

Good to have

• LLMs
• AWS
• GCP
• Azure
• MLOps
• NumPy