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Senior AI Trainer

$50–$90/h

Global

Catalogue update: this role is no longer listed in the current Micro1 catalogue. Browse current AI Training opportunities.

About the role

Help improve robotics training data through detailed review of recorded robotic-arm activity. The work combines video labeling with precise temporal annotation.

Skills and focus areas

Video annotation · attention to detail · data labeling

What you will do

  • Identify the actions and outcomes shown in each recording.
  • Mark exact boundaries between movements and events.
  • Check labels against the footage and correct timing drift or inconsistent segments.
  • Resolve ambiguous cases with reviewers and apply quality feedback.

Experience and requirements

  • Exceptional concentration when reviewing visual material.
  • Ability to follow detailed grading rules and use video-annotation tools.
  • Consistent, accurate documentation and communication with project contributors.

Working arrangements

  • Remote contractor engagement.

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Future of work · September 2026

How big is the remote / hybrid opportunity?

Remote work is already huge — but the bigger story may be the hundreds of millions of jobs that could still move beyond geography.

Global remote and hybrid work opportunity infographic

Remote work already connects millions of people with companies they would never have been able to work for a decade ago. But compared with the size of the global labour market, it may still be early.

The interesting number is not only how many people work remotely today — it is how many roles could plausibly become remote or hybrid next.

The chart above starts with roughly 3.3 billion people employed worldwide. Around 300 million jobs are already remote or hybrid, while an additional pool of roughly 250 million roles could potentially move in that direction as technology, workflows and company culture continue to change.

Skills are becoming more portable

This matters because more work can increasingly be matched to expertise rather than location. AI training and evaluation are a good example: companies need lawyers, engineers, designers, editors, researchers, finance professionals and many other specialists to help improve AI systems.

For workers, that creates access to projects outside their local market. For companies, it expands the talent pool from one city or country to the world.

Explore remote opportunities →