- 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
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- Sprint based project that runs in 12-24 hour stretches based on client requirement.
Compensation
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- $400 per accepted task.
- Typical tasks take approximately 2–3 hours after ramp-up.
- Compensation is tied to accepted work.
Who Should Apply
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- 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. xysqume
- Experience supporting production-scale systems is preferred.
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📌 DevOps Engineer - AI Model Evaluator (Milano)
🏢 Mercor
📍 Milano
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