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.

Application & Onboarding Process

• Complete a short AI-led interview (approximately 15 minutes).

• If selected, you will be onboarded and invited to begin project work.