About the role
Evaluate the quality, correctness, and production-readiness of Kubernetes tasks used to train and evaluate a frontier AI lab's models. You'll assess cluster-operations scenarios, manifest correctness, and failure-mode troubleshooting — and provide clear, rubric-based written feedback. Basic Qualifications • 3+ years hands-on production Kubernetes experience (EKS/GKE/AKS or self-managed) • Deep understanding of cluster internals: CNI/DNS/ingress, PV/PVC storage, RBAC, and failure modes (CrashLoopBackOff, OOMKilled, scheduling/eviction) • Experience authoring and reviewing manifests / Helm chart
Experience
• 3+ years hands-on production Kubernetes experience (EKS/GKE/AKS or self-managed) • Deep understanding of cluster internals: CNI/DNS/ingress, PV/PVC storage, RBAC, and failure modes (CrashLoopBackOff, OOMKilled, scheduling/eviction) • Experience authoring and reviewing manifests / Helm charts and debugging live cluster incidents • Proficiency in Go, Python, or TypeScript. Preferred Qualifications • CKA / CKAD certification • Service-mesh, autosc
Selection process
Apply on the official platform. The listing does not describe further selection steps.
Eligibility
Not specified by the source