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Generalist Expert (UK/Europe)

$50–$70/h

Europe / United Kingdom

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

About the role

Apply broad professional judgment to evaluating AI-produced office materials. The assignment covers documents, presentations, spreadsheets and related outputs.

Skills and focus areas

Written Feedback · English · Attention to Detail · Written Communication · Machine Learning · Generalist (UK/Europe)

What you will do

  • Assess correctness, usefulness and presentation against project criteria.
  • Compare responses and identify omissions or inconsistent reasoning.
  • Write concise explanations for quality ratings.

Experience and requirements

  • An undergraduate degree.
  • Excellent English reading and written communication.
  • Careful independent working and confidence with common office applications.
  • Prior machine-learning work is not required.

Working arrangements

  • Applicants must be based in the UK or Europe.

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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 →