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Quality Assurance Intern; Remote

Remote / Online - Candidates ideally in
Boise, Ada County, Idaho, 83701, USA
Listing for: Joblet-AI
Part Time, Apprenticeship/Internship, Remote/Work from Home position
Listed on 2026-11-07
Job specializations:
  • Quality Assurance - QA/QC
    Data Annotation/ AI Labeling
Salary/Wage Range or Industry Benchmark: 39000 - 77000 USD Yearly USD 39000.00 77000.00 YEAR
Job Description & How to Apply Below
Position: Quality Assurance Intern (Remote)
  • Location
    :
    Remote from US, CA, UK, IE, AU, NZ
  • Engagement Type:
    Freelance / Hourly Contract

Applicants must currently reside in Australia, Canada, Ireland, New Zealand, the United Kingdom or the United States.

Overview

We are looking for methodical people who spot observable problems and apply checks consistently. You will check basic examples against the rubric and note clear quality problems while evaluating AI-generated voice, image and video content. This opportunity is remote, with flexible hours and assignments based on project availability. Students, recent graduates and working professionals are welcome to apply.

Key Responsibilities
  • Check basic examples against the rubric and note clear quality problems.
  • Compare paired outputs for errors, missing details, clarity and prompt alignment.
  • Explain which observable details support your quality judgment.
  • Take part in English conversations with AI models when assigned to voice tasks.
  • Record your ratings using project guidelines and flag examples that are difficult to judge.
Requirements
  • Confident spoken English and clear written communication.
  • Ability to follow simple quality criteria with consistent attention.
  • Ability to repeat defined checks and flag uncertain cases consistently.
  • A computer, reliable internet and headphones, with a quiet space for voice-based tasks.
  • Ability to produce your own ratings and written explanations without using AI tools.

We welcome applications from qualified individuals of all backgrounds. Applicants are considered based on relevant skills, qualifications and project eligibility requirements, without discrimination on grounds protected by applicable law.

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