Want to get hired at MyRemoteTeam Inc?

AI Data Annotation QA

MyRemoteTeam Inc

HybridHybrid

Original Job Summary

About the Role: AI Data Annotation QA

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. Note: This role is specifically for AI Data Annotation QA, not Software QA.

What You’ll Do:

  • Carefully review provided data including text, images, or videos.
  • Verify and evaluate search result annotations and 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 Spanish.
  • Prior experience working 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, including asking clarifying questions when needed.
  • A genuine interest in technology and artificial intelligence.

How to Apply:

Interested candidates should send their resume (mentioning language proficiency) and fill the provided Google form. Contact details include email: sajid.ahmed@truelancer.com and WhatsApp: +91-9064877846.

Key skills/competency:

  • Data Annotation
  • Quality Assurance
  • AI Training
  • Data Labeling
  • Review
  • Verification
  • Attention to Detail
  • Logical Thinking
  • Spanish
  • Communication

How to Get Hired at MyRemoteTeam Inc

🎯 Tips for Getting Hired

  • Tailor your resume: Highlight AI data annotation and QA experience.
  • Emphasize Spanish skills: Clearly mention language proficiency.
  • Detail relevant projects: Include AI and labeling experiences.
  • Prepare for feedback: Be ready to discuss quality checks.

📝 Interview Preparation Advice

Technical Preparation

Review AI annotation tools and platforms.
Practice data quality assessment techniques.
Familiarize yourself with labeling guidelines.
Study common errors in AI outputs.

Behavioral Questions

Describe a time you ensured data accuracy.
Explain handling unclear instructions in a project.
Share an example of detailed feedback provision.
Discuss managing multiple guidelines concurrently.