Remote Hindi Audio Transcript Editor for AI Training

Alignerr Corp.; Greater London; Remote; GBP 17,000 - 28,000; Part time

Benefits offered by this job

Fully remote

Flexible schedule

Job summary

Alignerr is seeking Hindi Audio Transcript Editors for remote, hourly contract work in the UK and globally. You will clean up and polish transcripts, ensuring every word, timestamp, and formatting rule is exact. The role emphasizes meticulous listening, accuracy, and the ability to work independently on a flexible schedule.

No prior AI experience is required, making this ideal for native Hindi speakers who value precision and consistency across large volumes of transcript data.

Qualifications

• Native-level fluent Hindi with strong listening comprehension.
• Exceptional attention to detail and accuracy at the word level.
• Ability to verify timing and alignment precisely with audio.
• Ability to follow detailed style guides and formatting rules.
• Self-motivated and reliable for asynchronous, freelance work.

Responsibilities

• Listen to Hindi audio recordings and review transcripts for accuracy.
• Correct misheard words, missing segments, and spelling errors.
• Verify and adjust word-level timing and alignment to the audio.
• Apply style and formatting guidelines consistently across tasks.
• Flag ambiguous audio or overlapping speech for review.
• Maintain high quality across large volumes of transcript data.
• Work independently and on a flexible schedule.

Skills

Hindi fluency

Attention to detail

Listening skills

Formatting accuracy

Self-motivated

Tools

Transcription software

Job description

Alignerr is seeking Hindi Audio Transcript Editors for remote, hourly contract work in the UK and globally. You will clean up and polish transcripts, ensuring every word, timestamp, and formatting rule is exact. The role emphasizes meticulous listening, accuracy, and the ability to work independently on a flexible schedule.

No prior AI experience is required, making this ideal for native Hindi speakers who value precision and consistency across large volumes of transcript data.