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Korean Audio Transcription Expert
Job in
Northern, Floyd County, Kentucky, USA
Listed on 2026-10-01
Listing for:
OpenTrain AI, Inc.
Full Time, Part Time
position Listed on 2026-10-01
Job specializations:
-
Language/Bilingual
English Speaking, Data Annotation/ AI Labeling
Job Description & How to Apply Below
You will prepare accurate Korean and English audio transcripts for AI training. The work includes checking transcripts, adding audio metadata, and keeping files consistent with project guidelines.
- Transcribe audio containing Korean and English speech.
- Review, edit, and proofread transcripts for accuracy.
- Add relevant metadata and contextual notes to audio files.
- Follow style guides, project specifications, and quality standards.
- Work with project coordinators as guidelines and requirements change.
- Complete assignments within established timelines.
- Share feedback about workflows and transcription tools.
This is a remote, part-time contractor role. Prior AI experience is not required, but you should have professional transcription experience and strong Korean language skills.
- Pay: $20-$36 per hour in USD, based on experience.
- Schedule:
At least 10 hours per week and less than 20 hours per week. - Location:
Fully remote from eligible countries for this role. - Language:
Native or bilingual Korean, with strong spoken and written comprehension. - You must also understand the English content in the recordings.
- Professional experience with accurate audio transcription is required.
- Familiarity with standard transcription tools or platforms is required.
- Strong attention to detail and written and verbal communication skills are needed.
- You should be able to manage multiple assignments, meet deadlines, and adapt to changing requirements.
- Experience in AI training, data annotation, or language resource development is helpful but not required.
AI training is the human work behind systems that understand language, audio, images, and text. People who bring strong language skills and careful review experience help create reliable examples for these systems, which is why specialized contributors are paid for their expertise.
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