TransPerfect is hiring a
Language Data Annotator - Portuguese, Remote - Canada

Summary

The job description is for a Language Data Annotator position based in Canada that requires fluency in Portuguese. The role involves speech or text recognition and other areas of human-machine interaction related to languages. The job is full-time, flexible schedule, and remote, but candidates must be located in Quebec, Ontario, or Alberta.

Requirements

• Idiomatic fluency in Portuguese
• Eligible to work in Canada
• Must be of legal age (18+)
• Great reading and comprehension skills
• Ability to meet daily KPI's
• Excellent time management skills
• Ability to work independently
• Flexibility to respond and react to changing priorities, quickly and efficiently
• Ability to track, analyze, and report issues
• Full-time availability (40 hours/week) for duration of the project
• Ability to understand and implement feedback
• Detail-oriented and comfortable with repetitive tasks

Responsibilities

• Transcription - create written copies of live speech or dictated audio
• Data labeling - identify and label the properties of what you transcribe
• Data classification - categorize provided data into different criteria
• Data entry - following provided company guidelines, input the data and information

Benefits

• Work Location. : Remote, candidates must be located in Quebec, Ontario, or Alberta
• Work Schedule. : Full-time (up to 40 hours/week), Monday – Friday; Flexible schedule
• Engagement Model. : Employment; fixed-term/temporary
• Project Duration. : until June 30th, 2024 (highly extendable)
• Start Date. : ASAP
• DataForce by TransPerfect is part of the TransPerfect family of companies, the world’s largest provider of language and technology solutions for global business, with offices in more than 100 cities worldwide
• We offer high-quality data for Human-Machine Interaction to some of the most prestigious technology companies in the world
• Our department focuses on gathering, enriching and processing data for Machine Learning in different AI domains