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Junior AI Player Skill Rating Drift Auditor

Leah Nguyen

Full-time · Job · Los_Angeles

About the role

As a fully async team spread across multiple time zones, we believe great engineers do their best work when trusted with a clearly scoped, measurable problem, even early in their career. Our matchmaking fairness models assume skill ratings stay meaningful over time, but ratings can drift or inflate as the player base and meta evolve. You will build auditing tooling that flags when rating distributions are drifting in ways that hurt matchmaking quality. You'll work under a senior matchmaking engineer, learning how our rating systems work while contributing a tool the whole team relies on to catch problems early.

Responsibilities

  • Build auditing tooling flagging skill rating distribution drift over time
  • Analyze correlation between rating drift and matchmaking quality complaints
  • Support the senior team by producing regular rating health reports
  • Maintain statistical tests used to detect meaningful drift versus normal variance
  • Document drift patterns observed across different game modes

Requirements

  • Some Python and statistics coursework or personal project experience
  • Interest in game systems and player-facing fairness
  • Comfortable working with large-scale player behavior data
  • Eagerness to learn from a senior matchmaking engineer

Benefits

  • Fully remote, async-first team
  • Mentorship from a senior matchmaking engineer
  • Health insurance
  • Clear path to a full game systems engineering role

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Categories

AI & Machine Learning Engineers

Skills

python statistics

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

AI & Machine Learning Engineers

Skills

python statistics

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