AI training & evaluation
Kubernetes Task Auditor
Mercor
Evaluate the quality, correctness, and production-readiness of Kubernetes tasks used to train and evaluate a frontier AI lab's models.
- Work arrangement & location
- Remote · Current location: United States
- Engagement
- hourly
Location and residence requirements
- Current location
- United States
Employer’s location wording: Remote — United States
- Software Engineering
Employer description and requirements
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 charts and debugging live cluster incidents • Proficiency in Go, Python, or TypeScript
Preferred Qualifications • CKA / CKAD certification • Service-mesh, autoscaling, and observability experience (Istio, HPA, Prometheus/Grafana) • Prior SRE / platform-engineering or task-grading experience