Remote Video Annotation Specialist for AI and Robotics

SaidGig

New York (NY)

Remote

USD 21,000 - 110,000

Full time

4 days ago
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Job summary

SaidGig is seeking detail-oriented professionals to help improve AI systems by annotating robotics and human-activity videos with precision. You will review clips, apply rubrics, and produce high-quality annotations that capture actions, movement, and interactions.

This remote contract role involves refining AI-generated annotations, identifying subtle differences in movement and object interactions, and documenting decisions clearly to support scalable machine learning.

Qualifications

  • Experience with video annotation or a closely related review task.
  • Strong attention to detail and quality-assurance skills.
  • Clear written communication skills.
  • Robotics domain knowledge.

Responsibilities

  • Review and analyze short videos of robots or people performing actions against written instructions.
  • Assess whether actions are accurate and complete based on defined end states and project guidelines.
  • Compare video samples to determine which best fulfills a specified instruction.
  • Refine, correct, or expand AI-generated annotations, including action boundaries, descriptions, and feedback points.
  • Identify subtle differences in movement, object interactions, and action sequences.
  • Document observations and decisions clearly in writing.
  • Apply detailed rubrics consistently to maintain annotation quality.

Skills

Video annotation experience
Attention to detail
Quality assurance
Clear written communication
Robotics knowledge

Job description

SaidGig is seeking detail-oriented professionals to help improve AI systems by annotating robotics and human-activity videos with precision. You will review clips, apply rubrics, and produce high-quality annotations that capture actions, movement, and interactions.

This remote contract role involves refining AI-generated annotations, identifying subtle differences in movement and object interactions, and documenting decisions clearly to support scalable machine learning.

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