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Software Engineer, C — Codebase Q&A

$130/task

Global

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

About the role

Build rigorous repository-exploration tasks that teach AI agents to understand unfamiliar C software.

Skills and focus areas

Software Engineering · PostgreSQL · Git · System Design · English · Tax

What you will do

  • Investigate a supplied repository at a specified commit and verify behavior using runtime evidence.
  • Refine engineering questions, scoring criteria and reference solutions.
  • Run the validation workflow and address expert review feedback.

Experience and requirements

  • At least three years of professional software engineering with substantial production C.
  • Confidence navigating large codebases and explaining system behavior.
  • Precise written English and practical debugging skills.

Working arrangements

  • Remote asynchronous work in the client’s task environment.
  • Payment is $130 per approved task.

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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 →