HR Workflow Benchmark Design Expert

You will turn real HR and people operations work into benchmark tasks that test whether AI systems can follow policies, interpret documents, and make sound decisions. The tasks should require judgment and careful use of source materials, not simple information lookup.

• Design tasks based on payroll operations, workforce planning, HR policy application, and employee lifecycle processes.
• Create or source supporting materials such as HR policies, payroll reports, headcount data, and employment agreements.
• Write clear instructions and objective grading standards so qualified reviewers can reach consistent conclusions.
• Identify tasks that are ambiguous or cannot be graded reliably.
• Deliver approved benchmark work at the required quality level.

What it pays and takes

This is part-time contract work for an experienced HR or people operations professional. The role requires practical knowledge of HR workflows and the ability to turn that knowledge into clear evaluation tasks.

• Pay: $45 to $90 per hour.
• Time: Less than 20 hours per week.
• Location: Open to candidates in the countries listed for this role across the Americas, Europe, Africa, Asia, and the Middle East.
• Language: Strong written and spoken English at B2 level or higher.
• Experience: At least five years of hands-on responsibility in payroll, workforce planning, HR policy, or employee lifecycle operations.
• Required background: Experience creating or applying structured standards such as HR policies, payroll checklists, process documentation, compliance frameworks, or training assessments.
• Work style: Comfortable using spreadsheets, reports, and policy documents at the same time.
• Helpful: SHRM, CIPD, PHR, or an equivalent HR certification.
• Helpful: Experience with AI or large language model evaluation, although prior AI experience is not required.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work is the human side of building artificial intelligence. People prepare examples, review model outputs, and create evaluation standards so AI systems can handle real tasks more accurately. Experienced professionals are needed when the work depends on specialized judgment, such as applying HR policies or evaluating complex workflows.