You will test a healthcare technology product by following assigned clinical workflows and predefined product-testing activities. Your feedback will help assess whether the product is usable, functional, and relevant to practical healthcare settings.
- Follow assigned product-testing activities and clinical workflows accurately.
- Evaluate usability, functionality, and relevance to clinical practice.
- Identify potential issues and recommend improvements using clinical judgment.
- Submit structured feedback within the required timelines.
What it pays and takes
This is a short-term, project-based remote engagement for physicians in the United States. The role is part-time with flexible scheduling.
- Pay: No rate is provided in the role details.
- Time: 20+ hours per week.
- Location: Open to candidates in the United States.
- Education: MD or DO degree from an accredited medical institution.
- Licensing: Active and unrestricted medical license in the United States.
- Certification: Board certification in a recognized medical specialty.
- Experience: At least three years of relevant clinical experience and current or recent medical practice in the United States.
- Skills: Comfort with digital healthcare tools and structured feedback.
- Helpful background: Experience with EMR, EHR, or HIS systems, digital healthcare workflows, clinical decision-support tools, AI-enabled healthcare applications, clinical research, product testing, or healthcare technology projects.
- Relevant specialties include internal medicine, family medicine, pediatrics, emergency medicine, cardiology, neurology, endocrinology, hematology and oncology, nephrology, and infectious diseases.
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, including reviewing products, rating outputs, and giving structured feedback. Medical professionals are valuable for healthcare projects because their clinical judgment helps assess whether technology is accurate, useful, and appropriate for real-world practice.