Remote Cantonese Audio Generalist Evaluator Expert - ...

Mercor is seeking a Cantonese 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 Cantonese and English and enjoy translating complex audio and visual information into precise, well-structured text. Responsibilities Transcribe and Optimize Audio & Video Listen to, analyze, and transcribe audio and video content in Cantonese following detailed constraints and instructions. Produce high"‘quality written outputs, with supporting work in English when required. Ensure clarity, accuracy, and strict adherence to formatting and stylistic guidelines. 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 Cantonese and English. Document standards to ensure consistency across reviewers and model evaluations. Conduct Model Testing and Grading Run prompts through language models and assess generated outputs. Evaluate responses against predefined criteria for accuracy, completeness, and instructional clarity. 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. Fluency in Cantonese and English (spoken and written). Available to commit 10-20 hours per week. Preferred Qualifications College students or recent graduates. Background in linguistics, humanities, social sciences, or technical fields. Prior experience with transcription, annotation, evaluation, or research workflows. Interest in AI, language models, or applied research environments. Additional Role Details Work in a structured, goal-oriented project environment with clear tooling, guidelines, and support. Gain hands"‘on exposure to real-world AI research and evaluation workflows. #J-18808-Ljbffr

Created: 2026-05-09