Quality control specialist for AI/ ML with Portuguese (Brazil) language

About the Project TSMG is looking for Quality control specialists to support an AI language project focused on improving speech recognition systems. As a QC contributor, you will review completed language annotation tasks and ensure that AI-generated transcripts have been accurately converted into natural, readable display text according to the project guidelines. You will focus on identifying and correcting formatting, punctuation, capitalization, and text normalization issues. What You Will Do - Review completed Display Transcription tasks for accuracy and consistency. - Compare the Display Transcription against the original lexical transcript and project guidelines. - Verify the correct use of: - punctuation; - capitalization; - numbers, dates, times, and currencies; - abbreviations and other text normalization rules. - Ensure that the original words and meaning have been preserved. - Identify and correct formatting or guideline-related errors. - Use the reference audio when necessary to verify ambiguous cases. - Apply project-specific quality standards consistently. - Provide accurate feedback and flag recurring issues when required. - Complete assigned QC tasks within project deadlines and productivity targets. Requirements - Excellent written skills in the target language.

- Strong attention to detail and accuracy. - Good understanding of punctuation, capitalization, and written language conventions. - Ability to identify inconsistencies and errors in formatted text. - Ability to follow detailed guidelines and apply them consistently. - Basic computer skills and a reliable internet connection. - Ability to work independently and meet quality and productivity targets. - Previous experience in transcription, proofreading, quality control, annotation, or linguistic projects is a plus. - Training and project guidelines will be provided before the project starts. What We Offer - Opportunity to contribute to the development of AI and speech recognition technologies. - Flexible project-based work. - Clear guidelines and training before starting. - The opportunity to gain experience in AI language data and quality control projects.