Identify bugs, edge cases, reliability issues, and failure modes.
Compare outputs from multiple frontier models and assess their strengths and weaknesses.
Apply professional engineering judgment to realistic infrastructure engineering scenarios.
Time Commitment
Sprint based project that runs in 12-24 hour stretches based on client requirement.
Compensation
$400 per accepted task.
Typical tasks take approximately 2–3 hours after ramp-up.
Compensation is tied to accepted work.
Who Should Apply
2+ years of professional DevOps, SRE, or Cloud Engineering experience.
Experience with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD pipelines, or observability tooling.
Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
Ability to evaluate model-generated infrastructure and reliability engineering solutions.
Experience supporting production-scale systems is preferred.
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📌 DevOps Engineer - AI Model Evaluator - Milano, Lombardia, Italy
🏢 Mercor
📍 Milano
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