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AI Label Efficiency Benchmark Developer

Jaltrix Data

Remote · $60k – $80k / year · Full-time · Posted 4 months ago

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About the role

Not all labeling tasks are equally hard, and not all annotators are equally accurate on all tasks. Matching the right annotator to the right task — and knowing how many annotations you actually need to get reliable labels — determines whether your labeling budget produces useful training data or expensive noise. We run a data annotation platform serving 120 ML teams. Our label efficiency benchmarks measure annotator performance by task type, quantify how annotation cost varies with task complexity, and model the marginal value of additional annotations for borderline examples. These benchmarks guide labeling budget allocation and annotator training investment. As a junior developer on the data quality team, you will maintain and extend the benchmarking pipeline: building statistical models that estimate label quality from agreement rates, and creating the dashboards that annotation managers use to allocate resources across active projects.

Fully remote.

Responsibilities

  • Build statistical models estimating label quality from inter-annotator agreement rates
  • Implement per-annotator performance tracking across different task types
  • Create dashboards for annotation managers showing efficiency and quality metrics
  • Maintain the benchmarking data pipeline processing annotation event logs
  • Design analysis scripts for marginal value of additional annotations
  • Document methodology for client reporting on label quality assurance

Requirements

  • 1+ year of Python development with data analysis experience
  • Statistical reasoning skills for agreement rate analysis and quality estimation
  • SQL proficiency for analytical queries on annotation event data
  • Interest in ML data pipelines and annotation quality
  • Clear documentation habits and attention to statistical correctness

Benefits

  • Fully remote
  • Health and dental
  • $1,500 learning budget
  • Mentorship from senior data quality engineers
  • Clear growth path

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Categories

Data Science & Analytics MLOps & AI Infrastructure

Skills

python sql pandas docker statistics

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

Data Science & Analytics MLOps & AI Infrastructure

Skills

python sql pandas docker statistics airflow

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