Data Entry Specialist @ Mercor
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Job Details
Company Introduction
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Role Overview
Position: Data Annotation Specialist – Contract, Remote Commitment: 20 hours per week through December with potential for extension. Work on improving AI systems by categorizing and labeling data using predefined taxonomies.
Responsibilities
- Synthesize information from large volumes of data.
- Annotate and categorize text, images, and other data according to guidelines.
- Apply predefined rubrics and taxonomies for quality outputs.
- Flag inconsistencies, ambiguities, or errors in datasets.
- Directly influence the improvement of AI systems.
Requirements / Qualifications
Must-Have Qualifications: Must be based in the United States, have the ability to synthesize high-volume information into structured formats, and excellent written communication skills.
Preferred Qualifications: Prior experience applying rubrics, taxonomies, or standardized guidelines to tasks.
Engagement Details
- Remote and asynchronous; contractors set their own schedules.
- US-based contractor rate: $40/hour.
- Payments issued weekly via Stripe Connect.
- Contractors are classified as independent service providers.
Application Process
Submit your resume, complete the Preference Selection Calibration Assessment, and expect a response in 3-5 business days.
Resources & Support
For interview process details, please check: Interview Process. For support, contact: support@mercor.com.
Key skills/competency
- Data Annotation
- Data Categorization
- Remote Work
- AI Systems
- Text Labeling
- Synthesis
- Communication
- Attention to Detail
- Rubrics
- Taxonomies
How to Get Hired at Mercor
🎯 Tips for Getting Hired
- Research Mercor's culture: Study their investment and team background.
- Customize your resume: Emphasize data entry and annotation experience.
- Prepare for AI assessments: Practice data categorization tests.
- Review guidelines: Understand standardized rubrics and taxonomies.