The work
You will review Vietnamese speech and explain your judgments in clear written English. Your feedback will help improve how AI systems understand and generate Vietnamese.
- Listen to Vietnamese audio clips and assess naturalness, fluency, pronunciation, intonation, and linguistic authenticity.
- Write concise feedback in English and explain the language factors behind each evaluation.
- Give consistent, detailed reasons for your ratings and flag unclear language content for clarification.
- Complete assigned audio reviews accurately and on time while maintaining high quality.
- Provide language insights that support better AI performance in Vietnamese understanding and generation.
What it pays and takes
This is a remote, part-time contractor role with flexible scheduling. Prior AI experience is not required.
- Pay: $30 to $65 per hour.
- Work arrangement: Remote contractor work with flexible scheduling.
- Location: Open to candidates across the listed countries in the Americas, Europe, Asia, Africa, and the Middle East.
- Language skills: Professional proficiency in spoken and written Vietnamese.
- English skills: At least B2 proficiency for written and verbal communication.
- Requirements: Strong attention to detail and the ability to explain nuanced language differences clearly.
- Useful background: Voice specialization, linguistics, phonetics, music, audio engineering, audio analysis, transcription, linguistic assessment, media, communications, or teaching.
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 5 screening questions.
About AI training work
AI training is the human work behind systems that understand language, speech, images, and other data. People prepare examples, review model outputs, and provide careful feedback so AI systems can improve.