The work
You will help improve large language models by applying frontline emergency medicine knowledge to clinical scenarios and AI-generated answers. Your feedback will focus on safe, accurate reasoning in high-acuity situations.
The work includes creating and solving advanced emergency medicine cases, reviewing model responses, identifying gaps, and explaining how responses can improve. You will also work with medical peers and AI researchers on clinical reasoning and response quality.
- Design and solve scenarios involving acute trauma, resuscitation, toxicology, rapid differential diagnoses, diagnostics, triage, and other urgent care situations.
- Evaluate AI responses for diagnostic accuracy, clinical judgment, evidence-based reasoning, empathy, and safety.
- Identify gaps in the model's understanding of emergency medicine presentations and procedures.
- Give structured expert feedback in clear, patient-friendly language.
What it pays and takes
This is a fully remote, part-time contractor engagement. The initial duration is one month, with a possible extension.
- Pay: Not provided in the role details.
- Time: 20 to 40 hours per week, at least four hours per day, with some overlap with Pacific Time.
- Location: Remote and open worldwide.
- Education: MD or equivalent medical qualification.
- Practice: Active medical practice within the last three or more years.
- Certification: Board certification or an equivalent qualification in Emergency Medicine.
- Expertise: Trauma, resuscitation, toxicology, acute care, diagnostics, and triage.
- Communication: Excellent written and spoken English, with the ability to explain complex medical reasoning clearly.
- Helpful background: Familiarity with digital medical tools and education from a leading institution.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training is the human work behind systems that learn from examples and feedback. In this role, medical expertise helps evaluate model answers and improve how AI handles clinical reasoning, safety, and communication.