Remote Senior AI Video Data Annotator

YO AI Labs

Roma

Remote

EUR 34,000 - 69,000

Full time

14 days+

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Job summary

YO AI Labs is seeking a Senior AI Trainer to support customer projects focused on improving AI systems through expert-level video annotation and data labeling. You will review robotic-arm footage, create precise annotations, and provide high-quality data to support model training.

No prior AI experience is required, and the role emphasizes independent remote work, strict quality standards, and collaboration with project teams to resolve ambiguities and maintain consistency across datasets.

Qualifications

  • Exceptional attention to detail when reviewing visual data.
  • Strong written and verbal communication skills.
  • Excellent time management and ability to work independently in a remote environment.
  • Analytical and problem-solving mindset.

Responsibilities

  • Review robotic-arm videos and identify key actions, events, and outcomes.
  • Apply detailed guidelines to tag and annotate video events accurately.
  • Mark precise start and end timestamps for actions, transitions, and outcomes.
  • Verify annotations for timing accuracy and correct inconsistencies or drift.
  • Use video annotation tools to create and submit high-quality datasets.
  • Collaborate with project teams to resolve ambiguities and maintain annotation consistency.
  • Participate in quality reviews and incorporate feedback to maintain standards.

Skills

Attention to detail
Communication
Time management
Analytical thinking

Tools

Video annotation tools

Job description

YO AI Labs is seeking a Senior AI Trainer to support customer projects focused on improving AI systems through expert-level video annotation and data labeling. You will review robotic-arm footage, create precise annotations, and provide high-quality data to support model training.

No prior AI experience is required, and the role emphasizes independent remote work, strict quality standards, and collaboration with project teams to resolve ambiguities and maintain consistency across datasets.

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