Mathematics AI Response Evaluation Specialist

The work

As a Mathematics AI Response Evaluation Specialist, you will review AI-generated mathematical answers and judge whether their reasoning is correct, clear, and relevant to the prompt. You will work with step-by-step solutions across pure and applied mathematics.

You will also identify calculation errors, gaps in methods, and conceptual mistakes. The role includes writing strong mathematical explanations and model solutions, then comparing several AI responses to determine which is mathematically and logically strongest.

• Review AI-generated math answers for correctness, reasoning quality, and clarity.
• Check calculations, proof structure, methodology, and conceptual validity.
• Fact-check quantitative claims and identify errors or missing reasoning.
• Write and refine mathematical explanations and model solutions.
• Rank and compare responses based on mathematical correctness and reasoning quality.

This is a part-time contractor role for people with strong mathematical training and clear English writing skills. Prior data labeling, RLHF, or AI model evaluation experience is helpful but not required.

• Pay: $70 per hour.
• Time: 20 or more hours per week.
• Work type:
  Part-time contract.
• Language:
  Excellent English writing and clear mathematical communication.
• Location:
  
  Applicants must be based in Bangladesh, Bhutan, Brazil, Cambodia, Germany, India, Indonesia, Malaysia, Nepal, Pakistan, Singapore, Sri Lanka, Thailand, the Philippines, the United States, Timor-Leste, or Vietnam.
• Education:
  
  An MS or PhD in mathematics, statistics, or a related field from a top 100 university.
• Knowledge:
  Strong command of pure and applied mathematics, proofs, modeling, probability, statistics, and optimization.
• Background:
  Research, analytical writing, debate, programming, or mathematics experience.
• Helpful experience:
  Developing or critically reviewing problem banks, proofs, textbook sections, research notes, or other complex math content.

AI training work uses human reviews, examples, and explanations to help artificial intelligence produce better answers. People with strong subject knowledge are paid to check accuracy, explain mistakes, and guide models toward clearer and more reliable results.