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AI Peer Study Group Matching Engineer

Xavier Tanaka

Full-time · Job · New_York

About the role

Our adaptive learning and knowledge gap diagnostic tools already personalize what an individual student studies next, but students keep telling us in surveys that they learn better with peers who are working through the same material at a similar pace. This role builds a matching system that groups students into small study groups based on current knowledge gaps, pace, and availability, then hands off to the platform team to build the group experience around it.

Responsibilities

  • Build matching models grouping students by knowledge gaps and pace
  • Analyze study group outcomes against solo learning benchmarks
  • Work with the platform team on group formation logic and constraints
  • Iterate on matching criteria based on student feedback surveys

Requirements

  • Some experience with matching, clustering, or recommendation problems
  • Comfortable with SQL and pandas for student engagement data
  • Interest in education technology and learning outcomes
  • Ability to work with sensitive student data responsibly

Benefits

  • Fully remote entry-level role
  • Structured mentorship program
  • Health insurance included
  • Clear growth path to mid-level engineer

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

AI Product & Strategy data science & analytics

Skills

python sql statistics pandas

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