The work
You will listen to Korean audio clips and assess how natural and fluent the speech sounds, whether it comes from a person or an AI model. You will explain your decisions in concise English notes and help improve AI systems that understand and produce Korean.
- Evaluate pronunciation, intonation, fluency, and linguistic authenticity.
- Identify cultural and language-specific nuance in Korean audio.
- Write clear English assessments and detailed reasons for your ratings.
- Apply language-quality guidelines consistently across assigned audio tasks.
- Clarify ambiguous language content or requirements with project coordinators.
- Complete audio review work accurately and on time.
What it pays and takes
Experience in translation, language instruction, linguistic quality evaluation, content localization, AI, or data annotation is helpful.
- Pay: $30 to $65 per hour.
- Work type: Remote, part-time contractor engagement.
- Location: Open to candidates in multiple countries across North America, South America, Europe, Asia, Africa, and the Middle East, including the United States, Canada, the United Kingdom, India, Japan, and South Africa.
- Language: Professional fluency in Korean and English, including written and verbal communication.
- Requirements: Strong English writing, careful and consistent judgment, and the ability to notice subtle differences in pronunciation, intonation, fluency, authenticity, and cultural context.
- You should be able to explain language-quality decisions clearly and manage deadlines in a remote work setting.
How it works
You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.
The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 3 screening questions.
About AI training work
AI training is the human work behind systems that understand language, audio, images, and text. People review examples, rate model outputs, and explain quality issues so AI systems can improve; language specialists are especially useful when judgments depend on fluency, culture, and subtle speech differences.