Language Lead - Hindi (Contract)
New
C
CartesiaVoice AI
Remote, Availability during some US Pacific business hours is preferredContract
Salary25 - 35 USD per hour
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Job Details
- Languages
- Hindi, English
- Required Skills
- Quality Assurance
Requirements
- Native-level proficiency in Hindi as spoken in Hindi.
- Experience with data annotation, transcription, or language quality assurance.
- Strong foundation in linguistics or a related field (phonetics, prosody, intonation).
- Strong written English proficiency.
- Conversational spoken English proficiency for meetings and calibration syncs.
- Ability to write clear, structured instructions and deliver actionable feedback.
- Proficiency with data and metrics such as inter-rater agreement scores and audit spreadsheets.
- Ability to work independently and manage feedback cycles and QA reviews.
- Experience writing or maintaining annotation guidelines or rubrics (preferred).
- Experience training, mentoring, or managing other annotators (preferred).
- Experience with audio evaluation, TTS, or STT (preferred).
- Experience working with distributed, remote teams (preferred).
Responsibilities
- Answer questions from annotators about guidelines, edge cases, or language-specific issues via an agreed project communication channel.
- Cascade new feedback, instructions, or rubric updates to annotators working on your projects.
- Listen to annotator-rated audio files and check whether their ratings and written feedback align with the rubric.
- Prepare written quality assessments for annotators with specific examples and recommendations.
- Listen to TTS output and provide ground truth assessments of pronunciation, prosody, and naturalness in your language.
- Update or expand sections of the annotation guidelines when you find gaps or edge cases.
- Prep and run calibration meetings with annotators.
- Hold office hours on a mutually agreed schedule during active studies.
- Develop onboarding materials and resources for new annotators.
- Write QA reports on annotation quality and calibration outcomes.
- Review production audio in your language and flag quality issues to the team.
- Investigate language-specific issues reported by customers and identify root causes.
- Audit datasets for linguistic accuracy, completeness, and consistency.
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