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AI Quality Inspector

Olivia Wang

Full-time · Job · Los_Angeles

About the role

Our visual inspection platform processes 12,000 images per hour per facility. But models are only as good as the data they're evaluated against. We need someone to own the evaluation side: building golden test datasets, running model accuracy audits, analyzing failure patterns, and maintaining the feedback loop between factory floor observations and model improvements. As a junior AI quality inspector, you'll review model predictions against ground truth, categorize error types, and build the dashboards that tell our ML engineers exactly where models struggle. You'll also manage the annotation pipeline — coordinating with labelers, defining quality standards, and validating annotation consistency. This isn't a modeling role — it's a quality role. But you'll learn more about production CV systems by studying their failures than most engineers learn by building them.

Responsibilities

  • Build and maintain golden test datasets for visual inspection model evaluation
  • Run model accuracy audits and categorize error patterns by defect type
  • Manage the annotation pipeline and validate labeling consistency
  • Create dashboards tracking model performance trends over time
  • Coordinate feedback between factory floor observations and ML team

Requirements

  • Python proficiency with pandas for data analysis
  • Basic understanding of computer vision concepts
  • Strong attention to detail and systematic analytical skills
  • SQL skills for querying evaluation databases
  • Interest in manufacturing quality or computer vision

Benefits

  • Fully remote — US West Coast hours
  • Mentorship from senior CV engineers
  • Health insurance
  • $1,500 learning budget

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch computer vision pandas sql

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