Location: Remote working in Brazil (a one-time visit to our São Paulo office is required to pick up the equipment) Work Schedule: Full-time, Monday to Friday, 8 AM to 5 PM PST (Pacific Standard Time) Experience:
Location: Remote working in Brazil (a one-time visit to our São Paulo office is required to pick up the equipment) Work Schedule: Full-time, Monday to Friday, 8:00 AM to 5:00 PM PST (Pacific Standard Time) Experience:
Please submit your resume in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not
Please submit your resume in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not
Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider-of-choice for 4 out of 5 of the world’s
AI Model Evaluator Remote (From Brazil) Contract Work: Remote | 8 hours/day | 5 days/week (working days may vary) Equipment: Candidate’s own laptop Mandatory ~2-hour assessment Job Description We are looking for Portuguese speakers based in
About the Project We are looking for native or near-native speakers to support an AI data annotation and translation project. The role involves reviewing, translating, and annotating content according to detailed guidelines to help improve the quality
At Toloka, we connect smart, curious people from around the world with freelance online tasks that train and improve artificial intelligence. What we do The Toloka Annotators connects individuals with Generative AI projects from leading tech innovators.
JOB DESCRIPTION Their day to day includes overseeing data annotation teams and workflows to maintain the highest levels of dataset integrity and quality. This will primarily involve auditing annotation outputs, onboarding and mentoring new hires, and analyzing