The work
You will help evaluate how AI handles real laboratory medicine work. Your tasks will follow the workflow from specimen receipt through result interpretation and will focus on accurate, safe professional judgment.
- Write realistic laboratory medicine scenarios for AI evaluation.
- Create reference answers that clearly explain the analytical reasoning behind each result call.
- Rate model responses for analytical accuracy and patient safety.
- Identify answers that sound reasonable but could lead to an unsafe or incorrect result release.
- Apply expertise in hematology, chemistry, microbiology, or blood bank work.
What it pays and takes
This is fully remote, asynchronous independent contractor work. The project has no fixed hours, and the structured schedule requires at least 20 hours per week.
- Pay: $65 to $95 per hour, paid weekly through Stripe.
- Schedule: At least 20 hours per week with no fixed hours.
- Location: Remote and open to candidates across multiple listed countries, including the United States, Canada, Australia, and the United Kingdom.
- Language: Professional written English.
- Certification: MLS(ASCP) or an equivalent credential, such as AMT MT.
- Experience: At least two years of clinical laboratory experience.
- Specialty: Depth in at least one department, including hematology, chemistry, microbiology, or blood bank.
- Writing: Ability to explain analytical reasoning clearly.
- Helpful background: SBB, SH, or SM certification; reference laboratories; transfusion services; molecular diagnostics; quality assurance; method validation; or CAP inspections.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site. OpenTrain is where people find AI training and data-labeling work, build a profile, and start applications; it does not employ or pay contributors for this role.
About AI training work
AI training work uses human expertise to create examples and review AI responses so models can perform better. Specialists are paid for this work because their professional knowledge helps identify errors that general reviewers may miss, especially when accuracy and safety matter.