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Math Tutor - Part Time Work From Home

Outlier

Nevada (IA)

Remote

USD 10,000 - 60,000

Part time

5 days ago
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Job summary

A leading expert platform is looking for advanced Math experts for a part-time, work-from-home Math Tutor role. You will evaluate AI-generated Math content, develop questions, and assess AI responses. Ideal candidates hold a Master’s or PhD in Math, with research experience preferred. Compensation ranges from $30 to $50 per hour, with potential for higher rates based on performance.

Qualifications

  • Research experience, such as peer-reviewed publications, patents, or conference presentations.

Responsibilities

  • Evaluate AI-generated Math content for accuracy and relevance.
  • Develop and answer Math questions to refine AI understanding.
  • Assess and rank AI responses based on scientific rigor.

Skills

Proficiency in English

Education

Master’s degree in Math
PhD in Math

Job description

Join to apply for the Math Tutor - Part Time Work From Home role at Outlier.

Outlier is the world’s leading expert platform, connecting over 100,000 contributors worldwide to improve AI models through expert human feedback. We collaborate with companies like OpenAI, Meta, and Microsoft to enhance generative AI capabilities.

We seek advanced Math experts to help AI interpret and solve complex problems by:

  1. Evaluating AI-generated Math content for accuracy and relevance.
  2. Developing and answering Math questions to refine AI understanding.
  3. Assessing and ranking AI responses based on scientific rigor.

Required Qualifications:

  • Master’s degree or higher in Math or related field (PhD preferred), including current students.
  • Research experience, such as peer-reviewed publications, patents, or conference presentations.
  • Proficiency in English reading and writing with minimal errors.
  • Bonus: AI model training experience (not required).

Compensation:

  • Rates range from $30 to $50 per hour USD, depending on location and expertise.
  • Potential for higher-paying research projects based on performance.
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