Finnish-Speaking Audio Transcription Expert

You will help prepare accurate Finnish speech data for language technology and AI training projects. The work combines transcription, linguistic annotation, quality review, and clear documentation of difficult audio or language patterns.

• Transcribe Finnish audio recordings accurately.
• Annotate, segment, and label linguistic data using project guidelines.
• Review and validate other contributors’ transcriptions.
• Identify unclear audio, ambiguities, regional dialect differences, and colloquial language.
• Document recurring transcription challenges and suggest improvements to working guidelines.
• Communicate clearly to resolve requirements and questions.
• Deliver assignments within agreed timelines and milestones.

What it pays and takes

This is an entry-level, part-time contractor role. Previous AI experience is not required, but you should be comfortable making careful judgments when following detailed linguistic instructions.

• Pay: $20 to $30 per hour.
• Work type: Part-time contract work.
• Language: Professional fluency in Finnish, including strong knowledge of regional dialects and colloquial language.
• Location: Open to candidates in AE, AR, AT, BD, BE, BH, BR, CA, CH, CL, CO, DE, DK, DZ, EG, ES, ET, FR, GB, GH, GR, ID, IN, IT, JO, JP, KE, KG, KW, KZ, LB, LK, MA, MX, MY, NG, NL, OM, PE, PH, PK, PS, PT, QA, SA, SG, TH, TN, TW, US, UZ, VN, and ZA.
• Preferred background: Experience in transcription, linguistics, or another language-related project.
• Useful experience: Familiarity with transcription platforms, linguistic annotation tools, or language datasets.
• Core requirements: Strong written and verbal communication, meticulous attention to detail, accurate work, and careful interpretation of complex instructions.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work uses examples prepared and reviewed by people to help artificial intelligence systems understand language and produce better results. Audio transcription and linguistic review are important because accurate speech data helps models handle real voices, dialects, and everyday language.