Content Reviewer

What You Will Do -

• Review and evaluate AI-generated responses, images, or text to ensure accuracy, clarity, and appropriateness
• Flag errors, inappropriate content, or policy violations following provided guidelines
• Provide simple feedback to improve AI model performance
• Ensure all reviews meet quality standards and deadlines
• Report recurring issues or edge cases to the project team

You are a good fit if

• Fluent in English with basic reading and writing skills (other languages are a plus)
• Detail-oriented with the ability to spot errors quickly
• Strong sense of responsibility and consistency in completing tasks
• No prior experience required — freshers and beginners can apply
• Familiarity with online tools or platforms is helpful, but not necessary

About Role

• Flexible workload

  — work from anywhere, on your own schedule

• High impact

  — your work directly supports top AI labs & Fortune 500 teams in bringing AI projects to life

• Clear ownership

  — know exactly what success looks like and have autonomy to deliver

• Growth potential

  — consistent high performers get opportunities to lead larger programs and mentor incoming team members

Interview Process

1. Complete a screening with Zara, our AI interviewer in English, to learn more about your background and experience.

2. Click on the Apply link and sign up.

3. Upload your resume and complete the ID verification.

4. After verification, go to the Home Page.

5. Click on “Start Interview with Zara” – the 15-min AI interview will be based on your resume.

6. Complete the interview to proceed with onboarding.

Payout

Shape the data and workflows that power frontier AI

• Engagement

  | Hourly, at-will contractor

• Schedule

  | Fully remote & asynchronous (min. 15 hrs/week)

• Pay Range (US)

  | $25 – $100 per hour

• Start Date

  | Rolling — staffed as projects launch

About Company

Labelbox builds the data engine that accelerates breakthrough AI. Our platform, expert services, and marketplace let teams iterate on data as nimbly as they iterate on code, enabling safer, smarter models in production. We’re backed by SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins, and trusted by leading research labs and enterprises worldwide.