Math Content Reviewer
$200,000 USD/year Pay is set based on global value, not the local market. Most roles = hourly rate x 40 hrs x 50 weeks 

United States, US
Fully-remote
full-time (40 hrs/week)
Flexible schedule
Long-term role

Math Content Reviewer   $200,000 USD/year

Description

Many education software products still mistake engagement for learning. They deliver content that captures attention but fails to consistently build student understanding. Evidence from explicit instruction research and multimedia learning theory offers a more precise path: students achieve better outcomes when instruction is structured, direct, logically sequenced, and designed to minimize extraneous cognitive load.

LearnWith.AI has adopted a more disciplined approach. Rather than viewing instructional video as a content challenge, the team frames it as a learning-outcomes challenge. This position ensures that every math video upholds rigorous standards for direct instruction, sound pedagogy, and learning science, so that scaling production does not compromise student comprehension.

This job requires someone who can review a lesson and rapidly identify whether the instructional sequence is producing genuine learning. You must be able to pinpoint weaknesses in clarity, pacing, modeling, formative assessment, and concept progression, then convert that analysis into precise written feedback. This is not a general content review position, a creative production role, or a broad curriculum role disconnected from evidence-based teaching.

You will work at the center of the product by defining the instructional standard across the video library. If you are deeply invested in whether students truly learn math, and you want that judgment to shape work at scale, this role offers you unusually direct influence.

What you will be doing

  • Review math videos using direct instruction and learning science frameworks, delivering clear approval or rejection decisions, actionable feedback, and embedded insights that continuously elevate instructional standards

What you will NOT be doing

  • General content review - assessing non-instructional or non-video materials without applying learning science or direct instruction frameworks
  • Subjective feedback - offering vague opinions on content quality that lack structured evaluation criteria

Key responsibilities

  • Serve as the quality gatekeeper for learning-science-aligned direct instruction math videos that reliably produce effective student learning outcomes

Candidate requirements

  • Experience teaching K–8 math or developing K–8 math instructional materials (e.g., lessons, units, practice sets, digital activities)
  • Experience assessing video-based instructional content and delivering written feedback
  • Familiarity with Cognitive Load Theory and Mayer's Multimedia Principles
  • Currently based in the United States

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Chris Hayes
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United States

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