Remote AI Data Labeler & Validator

The Elitejob; United States; Remote; USD 24,000 - 42,000; Full time

Benefits offered by this job

100% remote

Flexible working hours

Performance-based bonuses

Training and skill development

Job summary

The Elite Job is seeking meticulous, tech-savvy individuals to join our team as Remote AI Data Annotators. You will label, categorize, and validate image and text datasets to support AI training for global projects.

This fully remote role offers flexible hours, full training, and opportunities to work on diverse datasets. Prior experience is not required, and you can learn new tools while contributing to cutting-edge technology.

Qualifications

• Strong written English communication is required.
• Excellent attention to detail and ability to follow precise instructions.
• Ability to work independently and manage time effectively.
• Comfortable performing repetitive tasks with high accuracy.
• Basic computer literacy and familiarity with web-based tools and spreadsheets.

Responsibilities

• Label, categorize, and annotate image and text data according to project guidelines.
• Review and validate previously annotated data for accuracy and consistency.
• Follow detailed instructions to maintain high-quality annotation standards.
• Work with annotation tools and AI-assisted platforms provided by The Elite Job.
• Meet daily, weekly, or project-based productivity targets.
• Report issues or ambiguities in data to project leads.
• Collaborate with QA teams to refine annotation processes.
• Maintain confidentiality of sensitive datasets.

Skills

Strong English

Attention to detail

Independent work

Time management

Repetitive tasks with accuracy

Basic computer literacy

Willingness to learn tools

Job description

The Elite Job is seeking meticulous, tech-savvy individuals to join our team as Remote AI Data Annotators. You will label, categorize, and validate image and text datasets to support AI training for global projects.

This fully remote role offers flexible hours, full training, and opportunities to work on diverse datasets. Prior experience is not required, and you can learn new tools while contributing to cutting-edge technology.