Math Tutor - Work From Home - AI Trainer - Job Opportunity at Outlier AI
USD 30-50 per hour
Benefits
Flexible remote work schedule with complete location independence
Project-based compensation structure with performance incentives
Opportunity to work with cutting-edge AI technology
Professional development in AI/ML domain
Key Responsibilities
Evaluate and assess AI model outputs for mathematical accuracy and relevance
Develop and curate high-quality mathematical content for AI training
Provide expert review of AI-generated mathematical solutions and explanations
Contribute to improving AI model performance through structured feedback
Requirements
Education
Master's degree or higher in Mathematics or related field
Experience
Professional experience in mathematics
Required Skills
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Sauge AI Market Intelligence
Industry Trends
Salary Evaluation
The offered rate of $30-50/hour aligns with market rates for specialized AI training roles, though rates for PhD holders can exceed $75/hour. Annual earnings potential ranges from $62,400 to $104,000 based on full-time equivalent hours.
Role Significance
Typically part of a distributed team of 5-15 domain experts working with AI researchers and engineers
Senior subject matter expert position with direct impact on AI model development and performance
Key Projects
Success Factors
Market Demand
Very high demand with growing competition among AI companies for qualified mathematics experts who can evaluate and train AI models
Important Skills
Critical Skills
Beneficial Skills
Unique Aspects
Rare opportunity to influence AI development in mathematics education
Flexible work arrangement with high-impact potential
Combination of traditional mathematical expertise with cutting-edge AI technology
Potential to shape the future of automated mathematical instruction
Career Growth
6-12 months to establish expertise in AI training, 1-2 years for advancement to leadership roles
Potential Next Roles
Company Overview
Outlier AI
Outlier AI is a specialized AI development company focused on improving machine learning models through expert human feedback
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