Senior AI Data Trainer - Remote Video Annotation Expert

Yo Ai Labs; Santa Fe Capital; A distancia; ARS 83.717.000 - 156.969.000; A tiempo parcial

Descripción de la vacante

Yo AI Labs is seeking a Senior AI Trainer to support a customer project 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 AI model training.

No prior AI experience is required. As a remote contractor, you will work independently, apply detailed guidelines, and ensure timing accuracy across annotations while collaborating with project teams to resolve

Formación

• Exceptional attention to detail and accuracy 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.

Responsabilidades

• 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.

Conocimientos

Attention to detail

Communication skills

Time management

Analytical thinking

Descripción del empleo

Yo AI Labs is seeking a Senior AI Trainer to support a customer project 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 AI model training.

No prior AI experience is required. As a remote contractor, you will work independently, apply detailed guidelines, and ensure timing accuracy across annotations while collaborating with project teams to resolve