Art of Problem Solving

Art of Problem Solving

Remote Contest Math Instructor (part-time)

Remote (United States) · Part-time

No sponsorshipDetected 8 days ago
Problem SolvingCritical Thinking

About the role

  • Art of Problem Solving is looking for an Upper-Level Math Instructor to join their Virtual Campus team.
  • The AoPS Academy Virtual Campus is an after-school and weekend enrichment option for students.
  • Our Year-Round courses are offered late afternoons to evenings between 4pm ET and 10pm ET Monday through Friday and from 10am ET to 9pm ET on Sunday.

Requirements

  • Must have some experience teaching or tutoring students at the middle to high school level.

Nice to have

  • Experience with middle and high school math contests such as: AMC, AIME, MATHCOUNTS, USA(J)MO, IMO, etc.
  • A bachelor's degree in a STEM field is required.
  • A master's degree or higher in a STEM field is preferred.
  • Strongly preferred: Experience with middle and high school math contests such as: AMC, AIME, MATHCOUNTS, USA(J)MO, IMO, etc.

Skills

  • Teach enthusiastic middle and high school students in our online classrooms.
  • Work in small classes (average size 12) with top performing students who are passionate about learning and are motivated to succeed.

Compensation

  • Benefits and Compensation:

Benefits

  • Paid Sick Leave
  • 401K retirement plan
  • Eligible for discretionary bonus after 2 years
  • The class rates represent flexible work time, 15 minutes early arrival immediately before class, and actual class time.
  • AoPS Academy is a program of Art of Problem Solving (AoPS), a global leader in K-12 advanced education.
  • Since 2003, AoPS has trained hundreds of thousands of the country's top students through its online school, in-person academies, textbooks, and online learning systems.

Visa & Work Authorization

  • At this time we are only hiring instructors who are located in and authorized to work in the United States.

This listing is sourced directly from Art of Problem Solving's careers page and normalized into a canonical job model.