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AI Annotator Skill-to-Task Matching Engine Developer

Ruby Santos

Full-time · Job · Manila

About the role

Our active learning sampling and consensus algorithms pick the right examples to label, but right now any available annotator can be assigned any task, even when their historical accuracy on that task type is poor. You will build a matching engine that routes labeling tasks to annotators based on demonstrated skill per task category, improving label quality without adding review overhead. You'll work closely with our labeler fatigue detection team, since task routing needs to balance skill matching against workload distribution to avoid burning out your best annotators.

Responsibilities

  • Build a task routing engine matching labeling tasks to annotator skill profiles
  • Maintain Airflow pipelines that keep skill profiles updated from recent labeling outcomes
  • Coordinate with the fatigue detection team to balance skill matching against workload
  • Validate routing improvements against downstream label quality metrics
  • Document routing logic for the annotation operations team

Requirements

  • 3+ years building workflow or task-routing systems
  • Strong Python skills and experience with ETL pipelines
  • Comfortable orchestrating jobs with Airflow
  • Experience with human-in-the-loop or crowdsourced labeling systems a plus

Benefits

  • Fully remote position
  • Health insurance
  • Equity package
  • Flexible working hours across time zones

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Categories

Automation & AI Workflows

Skills

python etl airflow

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

Automation & AI Workflows

Skills

python etl airflow

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