Bilingual Audio Expert (Japanese)

You will review Japanese audio clips used to train AI systems. Your evaluations will help improve how AI understands and produces Japanese speech.

The work combines careful listening, structured ratings, and written explanations in English. You will assess speech and model output against project guidelines and explain the language factors behind each decision.

• Listen to Japanese audio and judge naturalness and fluency.
• Evaluate pronunciation, intonation, and linguistic accuracy.
• Write concise feedback in English with clear reasoning.
• Clarify unclear language content with project coordinators.
• Complete assigned reviews accurately and on time.
• Share observations that can improve Japanese language understanding and generation.

Relevant experience in audio, linguistics, phonetics, teaching, media, or communications can help, but the key requirements are strong language judgment and careful evaluation.

• Pay: $30 to $60 per hour.
• Languages: Professional fluency in Japanese with clear enunciation; English at B2 level or above.
• Location: Open to candidates in countries including Japan, the United States, Canada, the United Kingdom, Germany, France, India, Singapore, and Vietnam.
• Requirements: Strong attention to detail, clear written and verbal communication, and the ability to explain nuanced language differences.
• Helpful background: Voice specialization, linguistics, phonetics, music, audio engineering, audio analysis, transcription, or linguistic assessment.

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.

AI training is the human work behind systems that understand language, images, audio, and other data. Reviewers with strong language or subject knowledge help prepare examples and assess model results so these systems improve.