Data Annotator
@ MyRemoteTeam Inc

Hybrid
$60,000
Hybrid
Contractor
Posted 1 day ago

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XXXXXXXXX XXXXXXXXXXX XXXXXXXX****** @myremoteteam.com
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Job Details

About the Data Annotator Role

We’re expanding our AI data-labeling projects and are looking for Quality Assurance specialists to review, verify, and ensure accuracy in AI training datasets. This role is specifically for AI Data Annotation QA, not Software QA.

Role & Responsibilities

  • Carefully review provided data (text, images, or videos).
  • Verify and evaluate search result annotations and other AI-generated outputs.
  • Label or classify content based on detailed project guidelines.
  • Identify and flag factually incorrect, sensitive, inappropriate, or unclear content.
  • Ensure accuracy, consistency, and adherence to project standards.
  • Provide clear feedback where necessary.

Requirements

  • Fluent in Russian
  • Must be living outside Russia
  • Prior experience with AI companies/platforms (e.g., Outlier, Appen, Clickworker)
  • Strong logical thinking, fact-checking, and reasoning skills
  • Excellent attention to detail and ability to follow complex instructions
  • Strong communication skills with willingness to ask clarifying questions
  • A genuine interest in technology and artificial intelligence

How to Apply

Interested candidates can send their resume (with language proficiency mentioned) via email at sajid.ahmed@truelancer.com or reach out on WhatsApp at +91-9064877846.

Key skills/competency

  • Data Labeling
  • Quality Assurance
  • AI Training
  • Accuracy
  • Verification
  • Review
  • Logical Thinking
  • Communication
  • Detail-Oriented
  • Feedback
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How to Get Hired at MyRemoteTeam Inc

🎯 Tips for Getting Hired

  • Customize your resume: Tailor it to AI annotation criteria.
  • Highlight language skills: Emphasize Russian fluency clearly.
  • Show relevant experience: List AI platforms worked with.
  • Prepare for detailed questions: Practice data review scenarios.

📝 Interview Preparation Advice

Technical Preparation

Review AI annotation standards.
Familiarize with data labeling tools.
Practice data verification exercises.
Brush up on quality assessment methods.

Behavioral Questions

Describe a quality challenge you solved.
Explain your method for detail review.
Share examples of clear communication in tasks.
Discuss handling unclear instructions.

Frequently Asked Questions