Licensed Physician (MD/DO) - Freelance AI Trainer

Location: Bengaluru; Chennai; Hyderabad; Mumbai; New Delhi, India

**About the company**

**Paid per approved task, about $35/hr equivalent.** One flat rate for every approved task.

Built to fit around a clinical practice:

• Tasks estimated at about 10–20 hrs/week while the project is active; you choose when and how much to contribute
• Contribute anytime, from anywhere
• No patient contact, no malpractice exposure: you review written clinical cases
• All reviewers are license-verified physicians
• $50 one-time onboarding reward, paid once your first production task is approved

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. **Participation is project-based.**

**What this opportunity involves**

We’re looking for actively practicing, US-licensed physicians (MD/DO) living outside the US, with an active, unrestricted US medical license, to evaluate clinical EHR vignettes for a medical AI evaluation project. General and internal medicine are the main focus. On this project, contributors may:

• Evaluate clinical EHR vignettes paired with a question, a proposed answer, and a distractor “trap” answer across diagnosis and treatment tasks, spanning cardiovascular, nervous, hematologic, respiratory, digestive, urinary, reproductive, musculoskeletal, and integumentary systems;
• Score the clinical reasoning quality of benchmark items: vignette accuracy and completeness, whether the vignette gives the answer away, answer correctness and gradeability, and trap quality;
• Check whether the reasoning chain reaches the answer from vignette facts alone, correct reasoning traces, and write short rationales;
• Work within three independent blind reads, followed by physician adjudication. Real clinical complexity only. You’re improving the AI tools you’ll eventually use yourself.

If you’re a practicing physician ready to take on this challenging and engaging project, apply to take part!

**What we look for**

This opportunity is a good fit for US-licensed physicians living outside the US who are looking for a flexible, time-limited project they can fit around clinical practice. Ideally, contributors will have:

• Medical degree (MD or DO) and an active, unrestricted US medical license (verified at onboarding and re-checked monthly);
• Board certification or completed residency training, with recent direct patient care (attending-level preferred);
• Broad, multi-system diagnostic and treatment experience (internal, family, emergency, or hospital medicine);
• Strong clinical reasoning: differential diagnosis, next-step management, and application of evidence-based guidelines;
• Prior experience in medical AI evaluation, clinical content or exam-question review, or medical annotation/QA (a plus);
• Strong written English (C1+).

*This opportunity is not suitable for medical students, unlicensed medical graduates, non-physician clinicians (NPs, PAs, nurses, pharmacists), or non-clinical healthcare titles.*

**How it works**

Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid ​

**How to apply**

Please submit your CV in English and indicate your level of English proficiency.

**Project time expectations**

You decide when and how much to contribute. For this project, tasks are estimated at around 10–20 hours per week during active phases. This is an estimate, not a minimum or a guaranteed workload, and applies only while the project is active. Tasks are submitted within the project timeline and need to meet the listed acceptance criteria to be approved.

**Earnings**

Earnings are per approved task, at a **flat rate set to about $35/hr equivalent** based on estimated task time. There are no tiers or speed adjustments to the base rate. QA and adjudication tasks are paid at a higher rate.

• $50 one-time onboarding reward, paid once your first production task is approved.
• Incentives: additional earnings for high-quality approved tasks. Terms are shared in the project guidelines.