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AI Data Labeling Manager

Ruby Santos

Full-time · Job · Chicago

About the role

Every ML model is built on labeled data, and bad labels produce bad models. We manage data labeling operations for AI companies that need high-quality annotations at scale — image segmentation masks, text classification labels, entity extraction annotations, and more. Our team of 200 annotators across 3 countries handles 500,000 labeling tasks per month. As a junior data labeling manager, you'll sit between the AI teams and the annotators. You'll monitor labeling quality metrics, design quality control workflows, investigate disagreements between annotators, and build dashboards that give our clients visibility into annotation progress and accuracy. This is a data operations role, not a modeling role. You'll spend your time analyzing label distributions, flagging quality issues, and making sure the data that goes into ML training pipelines is as clean and consistent as possible.

Responsibilities

  • Monitor and report on labeling quality metrics across annotation teams
  • Design quality control workflows including consensus scoring and spot checks
  • Investigate inter-annotator disagreements and refine labeling guidelines
  • Build dashboards tracking annotation progress and accuracy for clients
  • Coordinate with ML teams on labeling requirements and priority changes

Requirements

  • Python proficiency with pandas for data analysis
  • SQL skills for querying labeling databases
  • Understanding of basic statistics for quality measurement
  • Strong organizational and communication skills
  • Interest in ML data quality and operations

Benefits

  • Fully remote — US time zones
  • Health insurance
  • Structured mentorship
  • Career path into ML data engineering or operations

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Categories

data science & analytics AI Product & Strategy

Skills

python sql pandas statistics

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

data science & analytics AI Product & Strategy

Skills

python sql pandas statistics

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