A model will hand you a pipeline and an infrastructure change that apply cleanly and quietly leave a security group open to the world, a state file that will corrupt on the next run, and a rollback path that does not exist. In production those mistakes page someone at 3am. Reasoning about the whole system is the job.
As a DevOps Engineer you'll evaluate how models handle CI/CD, infrastructure-as-code, and cloud operations, expose where their automation breaks, and write the answers a strong platform engineer would trust.
What you’ll actually do
Probe infrastructure reasoning across CI/CD, infrastructure-as-code, containers, and cloud config, and see where the model's automation falls apart.
Find the failures that matter : insecure defaults, broken state, missing rollbacks, and changes that pass CI and break prod.
Write the correct approach when the model falls short, with failure modes and recovery made explicit.
Roles this fits
Common backgrounds: DevOps Engineer, Site Reliability Engineer, Platform Engineer.
What we look for
Hands-on experience running CI/CD, infrastructure-as-code, or cloud operations.
Comfort with a major cloud and tools like Terraform, Kubernetes, or Docker.
Clear written English: your explanations are the training signal.
No degree required. We care about what you can do, not where you learned it.
Compensation
Up to $40 – $150+/hr depending on task difficulty and specialization. Many contributors add $10k–$100k+ a year; some make it their full-time income.
About DataAnnotation
DataAnnotation is where 100k+ experts train the world’s leading AI models. $150M+ paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.
How it works
Apply, pass the qualification assessment, then pick up paid projects whenever you want and get paid weekly.
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