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Kubernetes Task Auditor

Review Kubernetes manifests, Helm charts, and troubleshooting scenarios used to train and evaluate frontier AI models. Use production cluster experience in a flexible US-based contract role paying $70-$90 per hour.

OpenTrain AI

Coding & Software

Remote Hourly · $70–$90/hr

$70–$90/hr

Compensation

1 country

Eligibility

Entry

Experience

Sep 1, 2026

Posted

Open to applicants in

United States

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About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain helps people build careers in AI training and data labeling by connecting specialized professionals with projects where their expertise directly improves how advanced AI systems perform.

As a Kubernetes Task Auditor, you will bring practical platform engineering judgment to structured AI model evaluation. You will work remotely from the United States as an English-language contractor for 20 or more hours per week.

  • Contractor, part-time engagement
  • United States-based opportunity
  • English-language work
  • 20+ hours per week
  • Pay: $70-$90 per hour

About AI Training Work

AI training is the human side of building modern artificial intelligence. Technical specialists review examples, assess model-generated work, and explain what correct, safe, and production-ready results should look like.

Your evaluations will help train and assess frontier AI models on realistic Kubernetes operations. This work is a way to apply specialized engineering experience to cutting-edge AI development while contributing through flexible, remote project work.

  • Evaluate realistic technical scenarios and model outputs
  • Apply professional judgment through structured rubrics
  • Help improve the quality and reliability of AI systems
  • Work remotely with a flexible part-time schedule

The Kubernetes Task Auditor Role

OpenTrain is recruiting a Kubernetes Task Auditor to evaluate the quality, correctness, and production readiness of Kubernetes tasks used to train and assess frontier AI models. The role combines hands-on platform engineering judgment with precise, structured model quality evaluation.

You will review cluster operations scenarios, Kubernetes manifests, and troubleshooting decisions. Your feedback must clearly explain technical issues and the expected standard, drawing on experience with incidents in live Kubernetes environments.

  • Role focus: Kubernetes operations task evaluation
  • Review tasks for realism, correctness, completeness, and operational suitability
  • Assess whether proposed solutions are safe and production ready
  • Use established, rubric-based evaluation standards

What You'll Do

You will assess whether Kubernetes tasks accurately represent realistic cluster operations and production scenarios. You will also examine the technical decisions and proposed resolutions within each task.

  • Review Kubernetes manifests and Helm charts for correctness, completeness, and operational suitability
  • Evaluate troubleshooting approaches for CrashLoopBackOff, OOMKilled, scheduling problems, and eviction
  • Examine decisions involving CNI, DNS, ingress, PV/PVC storage, RBAC, and related cluster internals
  • Judge whether proposed solutions are safe and appropriate for production use
  • Write clear, consistent, rubric-based technical feedback
  • Explain technical issues and the expected standard for each evaluation

Required Experience and Skills

This role requires at least three years of hands-on production Kubernetes experience. The listing is classified as entry level in the source details, but the work itself requires substantial practical Kubernetes and incident-debugging experience.

  • At least three years of hands-on production Kubernetes experience
  • Experience with EKS, GKE, AKS, or self-managed Kubernetes clusters
  • Strong knowledge of cluster networking, DNS, ingress, persistent storage, RBAC, scheduling, and common failure modes
  • Experience authoring and reviewing Kubernetes manifests or Helm charts
  • Experience debugging incidents in live Kubernetes environments
  • Proficiency in Go, Python, or TypeScript
  • Ability to write clear, consistent, rubric-based technical evaluations

Helpful Background

The following experience is helpful but not required according to the role details. It can support your ability to evaluate complex Kubernetes tasks and production operations decisions.

  • CKA or CKAD certification
  • Experience with service meshes such as Istio
  • Experience with autoscaling such as HPA
  • Experience with observability tools including Prometheus and Grafana
  • Prior SRE experience
  • Prior platform engineering experience
  • Technical task grading experience

Why Work With OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. Creating an account is free, and your profile can help you present credible experience, discover projects aligned with your skills, and build a lasting AI training portfolio.

AI training and data-labeling work spans model evaluation, code review, technical feedback, and other specialist contributions. By applying your Kubernetes expertise here, you can participate in a fast-growing field at the intersection of engineering and artificial intelligence.

  • Apply your production Kubernetes expertise to frontier AI evaluation
  • Build a profile around specialized technical experience
  • Discover opportunities that match your professional skills
  • Develop a durable portfolio in AI training work

Compensation and How to Apply

This is a part-time contractor opportunity requiring 20 or more hours per week. Compensation is $70 to $90 per hour, and the role is open to candidates in the United States who can work in English.

Apply through OpenTrain to create your profile and be considered for this Kubernetes Task Auditor opportunity.

  • Hourly pay: $70-$90 USD
  • Time commitment: 20+ hours per week
  • Employment type: Contractor and part time
  • Location: United States
  • Language: English
  • Application: Through OpenTrain

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