Role Overview
Review Kubernetes tasks that support the training and evaluation of advanced AI models. You will assess cluster-operations scenarios, manifest accuracy, production readiness, and troubleshooting for common failure modes, then deliver clear written feedback using defined evaluation rubrics.
Key Responsibilities
- Evaluate the quality, correctness, and production readiness of Kubernetes tasks.
- Review cluster-operations scenarios, Kubernetes manifests, and failure-mode troubleshooting.
- Provide concise, rubric-based written feedback on task quality and technical accuracy.
Qualifications
- At least 3 years of hands-on production Kubernetes experience, including EKS, GKE, AKS, or self-managed environments.
- Deep knowledge of cluster internals, including CNI, DNS, ingress, PV/PVC storage, RBAC, and failures such as CrashLoopBackOff, OOMKilled, scheduling issues, and eviction.
- Experience authoring and reviewing Kubernetes manifests or Helm charts, and debugging live cluster incidents.
- Proficiency in Go, Python, or TypeScript.
Preferred Qualifications
- CKA or CKAD certification.
- Experience with service meshes, autoscaling, and observability tools, including Istio, HPA, Prometheus, and Grafana.
- Previous SRE, platform engineering, or task-grading experience.
Work Terms
- Remote, available to candidates located in the United States.
- Hourly engagement.
Compensation
- $70 to $90 per hour.
Kubernetes Task Auditor in Mayo at Unknown Company
This position is listed as full time and able to be worked remotely.