$ cat jobs/portuguese-brazil-audio-qa-annotation-specialist-matchatalent-208756f90aeb.json
Portuguese (Brazil) Audio QA Annotation Specialist
This role requires the candidate to work remotely on a part-time basis from Brazil. Client Overview Our client is a global artificial intelligence technology company that partners with leading AI research organizations and enterprise businesses to develop next-generation large language models, speech recognition systems, and multilingual AI solutions. Operating with a distributed global workforce, the company supports the advancement of cutting-edge AI technologies by engaging highly skilled freelance contributors across language, audio, coding, reasoning, and data annotation projects. The organization provides flexible remote opportunities for professionals worldwide to contribute to innovative AI development while working on high-impact projects that improve speech recognition, multilingual understanding, and human-computer interaction. Job Role The Portuguese (Brazil) Audio QA Annotation Specialist is a freelance project-based role responsible for reviewing, validating, and ensuring the quality of audio annotation outputs that support the development of advanced speech recognition and multilingual AI systems. This role is ideal for professionals with strong listening skills, excellent command of Brazilian Portuguese, and prior experience in audio annotation, transcription, voice quality evaluation, localization, or linguistic quality assurance. The successful candidate will evaluate audio recordings for accuracy, pronunciation, alignment, transcription quality, and annotation consistency while maintaining high quality standards throughout the review process. This is a flexible remote engagement rather than a traditional full-time or part-time employment opportunity. Key Responsibilities Review and evaluate audio recordings, transcriptions, and annotation outputs for quality, accuracy, and consistency. Verify pronunciation, speech clarity, linguistic accuracy, timing alignment, and annotation completeness. Identify quality issues and provide structured feedback to
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