Senior AI Data Trainer — Remote Video Annotation Pro

YO AI Labs; United States; Remote; DKK 583,000 - 777,000; Part time

Benefits offered by this job

Remote work

Job summary

YO AI Labs is seeking a Senior AI Trainer to support a customer project by reviewing robotic-arm footage, tagging events, and providing high-quality labeled data to improve AI models. This remote contractor role requires meticulous attention to detail and strong communication as you work independently.

You will annotate with timecode precision, follow strict guidelines, and collaborate with teams to ensure consistency and quality across datasets.

Qualifications

• Must have 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

Written and verbal communication

Time management

Independent in remote environment

Analytical mindset

Tools

Video annotation tools

Timeline-based labeling tools

Frame-level annotation

Job description

YO AI Labs is seeking a Senior AI Trainer to support a customer project by reviewing robotic-arm footage, tagging events, and providing high-quality labeled data to improve AI models. This remote contractor role requires meticulous attention to detail and strong communication as you work independently.

You will annotate with timecode precision, follow strict guidelines, and collaborate with teams to ensure consistency and quality across datasets.