Train AI on Clinical Reasoning.
The models shaping the future of AI are only as rigorous as the medical experts behind them. Apply your expertise where it matters, and get paid to do it.
Dr. Amara
As seen on
This is not busywork.
The most advanced language models still hallucinate drug dosages, confuse contraindications, and invent clinical guidelines. The clinicians who fix this today are building the tools they'll rely on tomorrow — one annotation at a time.
Three steps.
No overhead.
Apply & Qualify
Complete a short clinical reasoning assessment. We evaluate your ability to identify diagnostic errors, apply evidence-based guidelines, and catch unsafe recommendations. No CV required — your clinical judgment speaks.
Get Matched
Based on your training and assessment results, you're matched to projects in your areas of expertise. Cardiology, oncology, emergency medicine, pharmacology, radiology — you choose what fits your background.
Work & Get Paid
Complete tasks on your own schedule. Each task has clear clinical specifications and a defined scope. Payment is per-task, processed weekly, starting at $50/hour.
What you'll actually do.
Write a prompt
Craft precise clinical prompts designed to probe the boundaries of model reasoning — not trivia, but questions that expose flawed differential diagnoses, misapplied guidelines, and hallucinated
treatment protocols.
Review AI output
Evaluate model-generated clinical analysis line by line. Identify hallucinated drug interactions, misapplied diagnostic criteria, and logical gaps in pathophysiological reasoning.
Write the correct solution
Author a complete, evidence-based clinical analysis that demonstrates the correct reasoning. This becomes training signal for the next model generation.
Where models need you most.
These are the clinical domains where your expertise shapes AI into a safer, more useful tool for patient care, documentation, and research workflows.
Cardiology & Critical Care
Evaluate AI reasoning about acute coronary syndromes, heart failure management, arrhythmia classification, and hemodynamic monitoring. Verify claims about treatment algorithms, drug titration, and risk stratification.
Pharmacology & Drug Safety
Review model outputs on drug mechanisms, dosing protocols, contraindications, and interactions. Catch misidentified mechanisms of action, incorrect renal dosing adjustments, and overlooked black-box warnings — including errors in high-stakes dosing tools like gentamicin nomograms.
Diagnostic Reasoning & Imaging
Assess AI-generated differential diagnoses and lab value analyses. Verify sensitivity/specificity claims and catch inappropriate test ordering.
Emergency & Acute Medicine
Audit AI outputs used in clinical documentation and research workflows. Identify errors in clinic note summarisation, post-op dictation, and research assistance tools like citation retrieval and data summarisation for literature reviews.
Oncology & Pathology
Review model outputs on cancer staging, treatment protocols, biomarker interpretation, and pathology findings. Verify TNM classifications, treatment sequencing, and molecular marker significance.
A selective community of experts.
We require excellence, just as you would require in peer review. The researchers and academics on our platform aren’t here to tick boxes. They’re here because the quality standard matters to them.
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“This is evaluation by people who understand system behavior and edge cases. The focus is always on improving model reliability.”
Daniel
Research Engineer
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“Every decision is grounded in first-principles reasoning. The standards are comparable to what I’ve seen in academic and industrial research.”
Anita
Applied Scientist
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“This is annotation done by people who understand models, not just labels. The quality bar is high and enforced.”
Elena
Senior ML Engineer
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“The work demands subject-matter expertise. Decisions are justified, reviewed, and aligned to well-defined taxonomies.”
Stephen
Research Scientist
Clinical tasks completed weekly
Active medical contributors
Medical schools represented
Built for people who think in differentials.
Medical Students
MS3/MS4 and graduate medical students with strong clinical foundations and diagnostic reasoning skills.
Residents & Fellows
Physicians in training looking for flexible, intellectually engaging work outside hospital hours.
Attending Physicians
Board-certified physicians applying clinical expertise to AI training data on their own schedule.
Clinical Researchers
PhDs and MD-PhDs with deep domain knowledge in pathophysiology, pharmacology, or clinical trials.
Frequently Asked Questions
Have questions? Here we answer the most common questions.
You’ll work on tasks that help AI perform better—like reviewing responses, checking accuracy, refining prompts, and rating outputs. No coding or technical background needed.
You’ll work on projects that improve AI systems, such as reviewing responses, checking accuracy, refining prompts, ranking outputs, and validating model behavior.
Projects include data labeling, annotation, evaluation, and quality review across text, images, and structured tasks—focused on improving real production AI systems.
This is ideal for people with strong reasoning skills, attention to detail, and subject-matter expertise who want flexible, remote work with real impact.
This is a flexible, task-based contractor role. There is no long-term commitment required, and you can work as much or as little as you choose.
Available projects vary but commonly include prompt evaluation, response ranking, factual accuracy checks, domain-specific review, and structured annotation tasks.
Researchers, students, professionals, and independent contributors who enjoy analytical work and want to contribute to advancing AI systems.
This is remote, asynchronous work focused on output quality rather than hours logged. Performance is evaluated based on contribution quality and consistency.
Get ahead in a changing workforce.
No recruiters. No interviews. Just meaningful work and real compensation.