Kubernetes Task Auditor
Listing checked September 1, 2026 · pay as published by Mercor
Overview
At Mercor, you will assess Kubernetes tasks that train a frontier AI lab's models. The work involves grading cluster-operation scenarios, checking manifest correctness, and judging whether failure-mode troubleshooting is realistic and complete. Each review ends with rubric-based written feedback that the AI team uses to improve model performance. This remote hourly role is open to candidates across the United States.
What You'll Do6
- 1Review Kubernetes task prompts and their expected solutions for technical accuracy and alignment with production practices.
- 2Trace cluster failure scenarios like CrashLoopBackOff, OOMKilled, and eviction to check if the stated root causes and fixes are correct.
- 3Audit Helm charts and raw manifests for errors in RBAC, storage, ingress, resource limits, and security context.
- 4Write rubric-based feedback that explains exactly what a task got right or wrong and what would make it production-ready.
- 5Flag ambiguous or misleading tasks that could bias model evaluation.
- 6Use Go, Python, or TypeScript to inspect or run task code when needed.
Requirements6
- 13+ years of hands-on production Kubernetes experience with EKS, GKE, AKS, or self-managed clusters.
- 2Strong grasp of cluster internals including CNI, DNS, ingress, persistent volumes, RBAC, and scheduling/eviction behavior.
- 3Proven ability to debug live cluster incidents such as CrashLoopBackOff, OOMKilled, and resource exhaustion.
- 4Comfort authoring and reviewing Helm charts and YAML manifests.
- 5Working proficiency in Go, Python, or TypeScript.
- 6Preferred: CKA/CKAD certification, Istio, HPA, Prometheus/Grafana, and prior SRE or platform-engineering work.
Who Should Apply
This role is for a production-tested SRE or platform engineer who can spot a wrong manifest or an unrealistic failure path at a glance. The work rewards people who enjoy writing precise, useful feedback and can apply the same rubric across dozens of tasks. Candidates who have only used Kubernetes through tutorials or managed services will find the depth required here uncomfortable. Rejections often happen when a candidate cannot describe a specific production incident they debugged, or when their Kubernetes knowledge is wide but thin on internals like RBAC, CNI, or persistent storage.
Salary Insight
The hourly rate is $70-$90, which sits above typical remote Kubernetes contract work and aligns with senior SRE or platform engineering experience.
Pay and demand for AI Training roles
AggregatedTypical pay
$70/hour
This role
$70–$90/hr
Most AI Training roles pay $40–$95 per hour. This role's pay falls inside that range.
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Hiring most right now: micro1 (309) · SME Careers (253) · Mercor (139)
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- data annotation10%
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Compensation
$70–90/hr
Required Skills
Application Tip
In your application, include a short incident postmortem that shows how you diagnosed a production failure, including the exact kubectl commands and manifest changes you used.
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