DevOps Engineer - AI Model Evaluator

05 ago - Turbigo
Obsidian

About the Role

- Mercor is partnering with a leading AI research lab to support a Frontier Code Agents project.
- Contributors help evaluate and improve frontier AI coding models through structured technical assessments.
- The work focuses on realistic infrastructure engineering workflows and model evaluation.
- Spots are limited and filling quickly on a first come, first serve basis.

What You'll Do

- Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.
- Review model-generated implementations involving cloud platforms, Kubernetes, CI/CD systems, observability, and infrastructure automation.
- 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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