Math Instruction Video Expert
$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 Instruction Video Expert   $200,000 USD/year

Description

A lot of education software still confuses attention with learning. The result is content that feels engaging in the moment but does not reliably build understanding. Research on explicit instruction and multimedia learning points in a clearer direction: students do better when teaching is structured, clear, well-sequenced, and designed to reduce unnecessary cognitive load.

LearnWith.AI is taking a stricter approach. Instead of treating instructional video as a content problem, the team treats it as a learning-outcomes problem. This role exists to make sure every math video meets a high bar for direct instruction, sound pedagogy, and learning science so that scale does not come at the expense of student understanding.

This job is for someone who can watch a lesson and quickly spot whether the sequence is doing real instructional work. You should be able to diagnose weaknesses in clarity, pacing, modeling, checks for understanding, and concept development, then turn that diagnosis into precise written feedback. This is not a general content review role, a creative production role, or a broad curriculum role untethered from evidence-based instruction.

You would sit close to the core of the product by shaping the standard for what good instruction looks like across the library. If you care deeply about whether students actually learn math, and you want that judgment to influence work at scale, this role gives you unusually direct leverage.

What you will be doing

  • Evaluate math videos against direct instruction and learning science principles, producing clear approval/rejection decisions, actionable feedback, and embedded insights that continuously refine instructional standards

What you will NOT be doing

  • General content review - reviewing non-instructional or non-video content without applying learning science or direct instruction principles
  • Subjective feedback - vague opinions on content quality without structured evaluation criteria

Key responsibilities

  • Be the gatekeeper for high-quality, learning-science-aligned direct instruction math videos that consistently drive effective student learning outcomes

Candidate requirements

  • Experience teaching K–8 math or designing K–8 math instructional materials (e.g., lessons, units, practice sets, digital activities)
  • Experience evaluating video-based instructional content and providing 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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