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Data Annotation Expert
Work sphere Global
HybridHybrid
Original Job Summary
Role Overview
Mercor is collaborating with a leading AI lab to contract detail-oriented generalists for a data annotation project. As a Data Annotation Expert, you will support the development of AI systems by categorizing and labeling diverse datasets using predefined taxonomies.
Key Responsibilities
- Synthesize information from large volumes of data.
- Annotate and categorize text, images, and other data following detailed guidelines.
- Apply predefined rubrics and taxonomies to produce structured, high-quality outputs.
- Flag inconsistencies, ambiguities, or errors in datasets.
- Contribute to the improvement of AI systems through consistent annotation work.
Ideal Qualifications
- Based in the United States.
- Ability to synthesize complex or high-volume information into structured formats.
- Strong critical reasoning, reading comprehension, and written communication skills.
- Prior experience applying rubrics, taxonomies, or standardized guidelines (preferred but not required).
More About the Opportunity
This is a remote and asynchronous role where contractors set their own schedules. The expected commitment is approximately 20 hours per week and the project duration is through the end of October, with a potential extension through year-end.
Compensation & Contract Terms
The role pays $45 per hour for U.S.-based contractors, with payments issued weekly via Stripe Connect. Contractors are classified as independent service providers.
Application Process
- Submit your resume to begin.
- Complete a Training Assessment.
- Typical response time: 1–2 business days.
Key skills/competency
- Data Annotation
- AI Systems
- Taxonomies
- Data Labeling
- Remote Work
- Attention to Detail
- Critical Reasoning
- Guidelines
- Contract Work
- Communication
How to Get Hired at Work sphere Global
🎯 Tips for Getting Hired
- Customize your resume: Align skills with data annotation requirements.
- Highlight remote work experience: Showcase self-management and discipline.
- Emphasize detail orientation: Provide examples of precise work.
- Research Work sphere Global: Understand their projects and AI focus.
📝 Interview Preparation Advice
Technical Preparation
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Review annotation software tutorials.
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Practice labeling diverse dataset samples.
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Study predefined taxonomies and rubrics.
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Test data consistency tools and guidelines.
Behavioral Questions
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Describe handling repetitive tasks under deadlines.
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Explain examples of attention to detail.
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Discuss managing time in remote settings.
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Outline approach to resolving data ambiguities.