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AI Synthetic Label Injection Detector

Ruby Santos

Freelance · Job · Chicago

About the role

Bad actors sometimes inject deliberately wrong labels into crowdsourced annotation batches to sabotage training data, and our current quality checks catch obvious errors but miss coordinated, subtle injection patterns. Small freelance engagement, clear scope. What we have today is a solid annotation quality pipeline that flags random errors well. What's missing is detection for coordinated label injection, where a small group of annotators systematically mislabel a specific category to poison downstream models. Your role is to build a detector that flags suspicious annotator behavior patterns, working closely with our labeling operations lead who will validate flagged cases before annotators are removed.

Responsibilities

  • Build a detector for coordinated label injection patterns
  • Flag suspicious annotator behavior for review
  • Analyze annotation batches for systematic mislabeling
  • Work with labeling operations on validation
  • Report detection accuracy on a rolling basis

Requirements

  • 1-2 years of experience with data quality or anomaly detection
  • Basic scikit-learn and pandas skills
  • Comfortable with freelance, project-based work
  • Attention to detail in behavioral pattern analysis

Benefits

  • Fully remote, freelance flexibility
  • Negotiable project-based rate
  • Potential for ongoing engagement
  • Direct access to labeling operations lead

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Categories

data science & analytics Automation & AI Workflows

Skills

python scikit-learn pandas

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Job Type

Freelance

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

data science & analytics Automation & AI Workflows

Skills

python scikit-learn pandas

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