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DevOps Engineer

$50–$100/h

Global

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

About the role

Create realistic infrastructure-engineering tasks that help evaluate AI performance. The project emphasizes technical correctness and reproducible solutions.

Skills and focus areas

Kubernetes · Terraform · CI/CD

What you will do

  • Develop scenarios involving deployment pipelines, containers, orchestration, infrastructure code and incidents.
  • Write working reference solutions with setup and validation instructions.
  • Find failures in AI-generated solutions and explain the correction.
  • Improve task quality through structured feedback.

Experience and requirements

  • At least three years in DevOps, SRE, platform or infrastructure engineering.
  • Practical automation and cloud-infrastructure expertise.
  • Clear technical writing and disciplined validation.

Working arrangements

  • Remote contractor role requiring at least 20 hours weekly.

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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 →