Experience

MD/DNB Radiology, NMC-registered

Skills

- MD/DNB Radiology

- Benchmark design
- Ground-truth labeling

- Adjudication protocols
- Inter-reader variability

- Model evaluation

Job Summary

- 5Cs AI is judged against what its radiologists say is correct. This role owns that standard. You will design the gold-standard benchmark datasets, adjudication protocols, and ground-truth labeling standards that Bionics models are measured against - turning clinical judgment into evaluation the Applied AI team can build to.
- You are an NMC-registered radiologist with rigorous reporting standards and an interest in how models fail. Any subspecialty is welcome; depth in MSK, neuroradiology, or chest imaging is particularly valued. You will not be working through a reading worklist - you will define what a correct read looks like, case by case, so model performance is measured against something real.
- The pitch is simple: your expertise, amplified. A single well-adjudicated benchmark case shapes the behaviour of models that read millions of scans. This is the radiologist who teaches machines what excellent looks like.
- We are strongly biased toward candidates who can join quickly. If your notice period is short, your application will move faster because these teams are being built now.

You Should Have

- MD or DNB in Radiology with active NMC registration
- Rigorous personal reporting standards and the ability to articulate why a read is correct, not just what the read is
- Comfort with structured criteria:



you can turn "I know it when I see it" into a written standard another radiologist can apply consistently
- Interest in how AI models behave and fail. You do not need to write code, but you need to reason clearly about sensitivity, specificity, false positives, false negatives, and calibration
- The temperament for adjudication: patient with disagreement, exact in documentation, and comfortable being the final word on ground truth Even Better If You Have

- Subspecialty depth in MSK, neuroradiology, or chest imaging
- Experience with reader studies, research methodology, or statistics: kappa, ROC analysis, cohort design
- Teaching or peer-review experience - you have already spent time explaining what separates an adequate read from an excellent one

- Prior exposure to AI model evaluation, annotation programs, or clinical quality assurance

Why 5C

- Your judgment scales. A benchmark you adjudicate once shapes model behaviour across every scan those models read

- You sit at the centre of the Applied AI team, not at its edge. Ground truth is the constraint everything else is built around
- 5C reads scans for 2,000+ hospitals and diagnostic centers, so the standards you set propagate through one of the largest radiology operations in the country

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Radiologist - Clinical Benchmarks (Bengaluru)
🏢 5C Network
📍 Bengaluru