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Hindi Audio Generalist Evaluator Expert; San Francisco Bay Area

Job in Phoenix, Maricopa County, Arizona, 85003, USA
Listing for: Mercor
Part Time position
Listed on 2026-07-16
Job specializations:
  • IT/Tech
    AI Evaluation, Data Annotation/ AI Labeling
Job Description & How to Apply Below
Position: Hindi Audio Generalist Evaluator Expert (San Francisco Bay Area)

Mercor is seeking a Hindi Audio Generalist Evaluator Expert to contribute to a high-impact audio AI research project with a leading research lab. In this role, you will work on transcription, annotation, and evaluation tasks that help train and benchmark advanced language models. This is a short-term, structured engagement ideal for candidates with strong academic or analytical backgrounds who are fluent in Hindi and English and are based in the San Francisco Bay Area
, enabling occasional in-person collaboration if required.

Job Responsibilities Transcribe and Optimise Audio & Video
  • Listen to, analyse, and transcribe audio and video content in Hindi, following detailed constraints and instructions.
  • Produce high-quality written outputs in Hindi, with supporting work in English when required.
  • Ensure clarity, accuracy, and strict adherence to formatting and stylistic guidelines.
  • Capture nuances such as tone, intent, formal vs. informal register, regional expressions, dialectal variations, and contemporary Hindi usage where relevant.
Define and Document Evaluation Standards
  • Establish clear expectations for correct and high-quality responses in general consumer audio contexts.
  • Develop detailed evaluation rubrics and grading guidelines in Hindi and English.
  • Document standards to ensure consistency across reviewers and model evaluations.
  • Identify linguistic nuances, grammatical complexities, colloquialisms, code-switching patterns, and edge cases specific to Hindi.
Conduct Model Testing and Grading
  • Run prompts through language models and assess generated outputs.
  • Evaluate responses against predefined criteria for accuracy, completeness, fluency, and instructional clarity.
  • Provide structured feedback to improve model performance in Hindi audio tasks.
Support Benchmarking and Quality Assurance
  • Participate in QA and review cycles to ensure tasks, rubrics, and outputs meet Mercor’s quality bar.
  • Maintain consistency and reliability before datasets are integrated into official benchmarks.
  • Collaborate with project leads to resolve ambiguities and improve task design.
Minimum Qualifications
  • Strong writing, editing, and critical thinking skills.
  • Ability to work independently, manage time effectively, and meet deadlines.
  • Native or near-native fluency in Hindi (spoken and written) and professional fluency in English.
  • Strong familiarity with spoken Hindi, regional vocabulary, dialects, and contemporary language usage.
  • Ability to accurately transcribe and analyse Hindi audio content across general consumer contexts.
  • Must be based in the San Francisco Bay Area.
  • Available to commit 10–20 hours per week.
Preferred Qualifications
  • College students or recent graduates.
  • Background in linguistics, humanities, social sciences, journalism, translation/localization, or technical disciplines.
  • Prior experience with transcription, annotation, localisation, evaluation, or research workflows in Hindi.
  • Familiarity with Hindi-English code-switching (Hinglish) and regional language variation.
  • Interest in AI, language models, or applied research environments.
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