Review AI-generated mathematical reasoning, apply clear rubrics, and explain your judgments in writing. This remote contractor role requires English fluency and strong mathematical or AI workflow expertise.
The Work
You will support AI training focused on mathematical reasoning workflows. The work uses mathematical proofs and AI agent workflow specifications to help systems learn from structured expert feedback.
You will review source materials and model outputs, assess them against project guidelines, and document evidence-based judgments. Clear explanations and consistent decisions will help improve model behavior across repeated review tasks.
- Evaluate model outputs using project rubrics.
- Review source materials and AI-generated responses against detailed guidelines.
- Explain your decisions clearly in written feedback.
- Maintain consistent quality across repeated evaluation tasks.
What It Pays and Takes
Compensation is handled through the OpenTrain project budget fields shown on the job page; no specific rate is provided in the listing. The role is a remote contractor position, and prior AI training experience is not required.
- Schedule: The role description calls for 40 hours per week, including four hours of overlap with Pacific Time. The structured listing also indicates 20+ hours per week.
- Location: Worldwide and remote.
- Language: Fluent English.
- Level: Entry level.
- Expertise: Relevant professional or academic knowledge of mathematical AI workflow engineering.
- Skills: Strong written communication, careful attention to detail, and the ability to follow detailed instructions and apply rubrics consistently.
- Work style: Comfortable working independently on remote contractor tasks.
How It Works
Apply on OpenTrain with your resume and 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 model responses and giving structured feedback. People with strong subject knowledge are needed to judge difficult outputs accurately and explain what better reasoning looks like.