Generalist Data Labeling Specialist
@ Call For Referral

Hybrid
$46,800
Hybrid
Part Time
Posted 22 days ago

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XXXXXXXXX XXXXXXXXXXX XXXXXX****** @callforreferral.com
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Job Details

Overview

A leading AI research initiative is seeking detail-oriented generalists to support the development and fine-tuning of advanced AI systems. As a Generalist Data Labeling Specialist, you will enhance AI model accuracy by labeling and classifying diverse datasets. This short-term, fully remote contract has the potential for extension based on project performance.

Key Responsibilities

  • Synthesize large volumes of information into structured outputs.
  • Annotate and classify text, images, and multimedia data.
  • Apply standardized rubrics and taxonomies for consistency.
  • Identify and flag errors, ambiguities, or inconsistencies in datasets.
  • Contribute to the evaluation and enhancement of AI systems.

Ideal Qualifications

  • Based in the United States.
  • Strong ability to process and structure complex information.
  • Excellent reading comprehension, analytical, and writing skills.
  • Prior experience in data labeling, content moderation, or taxonomy development is a plus.
  • Ability to work independently with flexible scheduling.

Project Timeline & Commitment

Start Date: Immediate Duration: Through October with potential extension through year-end Commitment: ~20 hours per week Schedule: Fully remote and asynchronous

Compensation & Application Process

Rate: $45 USD per hour Contract Type: Independent contractor Payments: Weekly via Stripe Connect To apply: Submit your resume and complete a short training assessment. Expect a response within 1–2 business days.

Key skills/competency

AI, Data Labeling, Annotation, Classification, Taxonomy, Remote, Contract, Detail-Oriented, Analysis, Structured Data

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How to Get Hired at Call For Referral

🎯 Tips for Getting Hired

  • Customize your resume: Highlight data labeling and annotation skills.
  • Research Call For Referral: Understand their AI research initiatives.
  • Prepare examples: Showcase successful data annotation projects.
  • Practice assessment: Review detailed training assessments.

📝 Interview Preparation Advice

Technical Preparation

Review data annotation tools and guidelines.
Practice dataset classification exercises.
Study rubric and taxonomy standards.
Run through error detection simulations.

Behavioral Questions

Describe managing independent remote work.
Explain handling deadline-driven tasks.
Discuss teamwork in asynchronous settings.
Share experiences with attention to detail.

Frequently Asked Questions