Want to get hired at Call For Referral?

Generalist Data Labeling Specialist

Call For Referral

HybridHybrid

Original Job Summary

About the Role

A leading AI research initiative seeks detail-oriented generalists to support advanced AI systems. In this role, you will help improve AI model accuracy and reasoning by categorizing, labeling, and structuring diverse datasets. Your work directly influences the quality, reliability, and interpretability of next-generation AI technologies.

Key Responsibilities

  • Synthesize large volumes of information into structured outputs.
  • Annotate and classify text, images, and multimedia data.
  • Apply standardized rubrics and taxonomies for quality labeling.
  • Identify and flag errors, ambiguities, or inconsistencies.
  • Contribute to enhancing AI reasoning and perception systems.

Ideal Qualifications

  • Based in the United States.
  • Strong ability to process and structure complex information.
  • Excellent reading comprehension, analytical, and writing skills.
  • Experience in data labeling, content moderation, or taxonomy development preferred.
  • Comfortable working independently with flexible scheduling.

Project Timeline & Compensation

Start Date: Immediate Duration: Through October with potential extension Commitment: ~20 hours/week, fully remote and asynchronous Rate: $45 USD/hour via weekly payments

Application & Onboarding Process

  • Submit your resume to begin the process.
  • Complete a short training assessment to demonstrate attention to detail.
  • Receive a response within 1–2 business days.
  • Mercor team reviews applications daily for rapid processing.

Key skills/competency

  • Data Annotation
  • Data Labeling
  • Content Moderation
  • Taxonomy Development
  • Analytical Skills
  • Attention to Detail
  • Remote Work
  • AI Systems
  • Data Structuring
  • Communication

How to Get Hired at Call For Referral

🎯 Tips for Getting Hired

  • Customize your resume: Highlight relevant labeling and data skills.
  • Research Call For Referral: Understand their AI initiatives and culture.
  • Prepare examples: Showcase data processing and annotation experience.
  • Practice assessments: Be ready for training evaluation tests.

📝 Interview Preparation Advice

Technical Preparation

Review data annotation tools.
Practice categorizing diverse datasets.
Familiarize with labeling rubrics.
Study taxonomy development basics.

Behavioral Questions

Describe your attention to detail.
Explain handling ambiguous instructions.
Share remote work experience examples.
Demonstrate independent problem-solving skills.