Devops Engineer - Ai Model Evaluator
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Job description
About the RoleNo deje pasar esta oportunidad, inscrÃbase rápidamente si su experiencia y habilidades coinciden con lo que se indica en la siguiente descripción.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 DoUse 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 CommitmentSprint based project that runs in *** 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 Apply2+ 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.xghoner Experience supporting production-scale systems is preferred.#J-***-Ljbffr
Requirements
scenarios.Time CommitmentSprint based project that runs in *** 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 Apply2+ 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. xghoner Experience supporting production-scale systems is preferred. #J-***-Ljbffr
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