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Teaching Specialist - AI Education Research

Call For Referral

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Original Job Summary

About the Role

The Teaching Specialist - AI Education Research is part of an experimental research project focusing on benchmarking and improving cutting-edge AI models through realistic teaching scenarios.

Key Responsibilities

  • Collaborate with researchers to develop realistic teaching scenarios.
  • Design and review teaching-style prompts, responses, and work products.
  • Provide feedback on logic, clarity, and educational value.
  • Work independently and in a small, flexible project team.

Ideal Qualifications

  • 3+ years teaching experience at middle/high school level in the US or Canada.
  • Strong online research and analytical skills.
  • Excellent written communication and attention to detail.
  • Ability to collaborate effectively and iterate on feedback.

Project Details

  • Start Date: ASAP
  • Duration: 6–8 weeks
  • Commitment: ~30 hours per week

Compensation & Contract

  • Pay: $50–$70 USD per hour based on experience
  • Bonus: Additional $20–$100/hr for top performers
  • Contract: Independent contractor (via Stripe Connect)

Application Process

Submit your resume and participate in a short AI-led interview to share your background, experience, and motivation for the role.

Key skills/competency

Teaching, AI, Research, Collaboration, Communication, Feedback, Online, Analytical, Curriculum, Independent

How to Get Hired at Call For Referral

🎯 Tips for Getting Hired

  • Customize your resume: Highlight your teaching and research experience.
  • Showcase online skills: Emphasize digital research and communication.
  • Practice prompt responses: Prepare for AI-led interview scenarios.
  • Research Call For Referral: Study their mission and project details.

📝 Interview Preparation Advice

Technical Preparation

Review AI research methodologies.
Practice designing teaching prompts.
Familiarize with digital collaboration tools.
Study online education analytics.

Behavioral Questions

Describe handling iterative feedback.
Explain remote team collaboration experience.
Discuss problem-solving under uncertainty.
Share examples of adapting teaching methods.