Kubernetes Engineer

Green Key Resources; Oregon; On-site; USD 150,000 - 190,000; Full time

Job summary

Green Key Resources is seeking a Kubernetes Platform Engineer in Oregon to design and operate scalable clusters for GPU-accelerated workloads, emphasizing reliability and multi-tenant isolation.

You will build operators, manage GPU resources, improve scheduling, and collaborate with ML/HPC teams. Proficiency in GitOps, IaC, and incident response is required. This role is based in Oregon with on-site work expectations.

Qualifications

• Experience administering Kubernetes clusters at scale.
• Hands-on with GPU resources and multi-tenant isolation.
• Proficient in GitOps and IaC workflows.
• Strong abilities in monitoring, incident response, and on-call readiness.

Responsibilities

• Design and operate highly available Kubernetes platforms for accelerated workloads.
• Develop custom Kubernetes operators and automation to streamline infrastructure services.
• Integrate and manage GPU resources within Kubernetes.
• Improve workload scheduling and resource utilization with Kubernetes scheduling capabilities and other schedulers.
• Collaborate with platform engineering, ML, HPC, and DevOps teams for high-throughput environments.
• Build observability, monitoring, and telemetry for cluster infrastructure and workloads.
• Enforce secure multi-tenant environments with RBAC, namespaces, and policy controls.
• Maintain infrastructure delivery pipelines using GitOps and CI/CD practices.
• Manage IaC and Kubernetes configurations with Terraform and Helm.
• Participate in capacity planning, performance tuning, production readiness, and incident response.

Skills

Kubernetes

GPU scheduling

GitOps

Terraform

Helm

Observability

Incident response

Tools

Terraform

Helm

Prometheus

Kubernetes manifests

Job description

• Design, build, and operate highly available Kubernetes platforms supporting accelerated and compute-intensive workloads.
• Develop and maintain custom Kubernetes operators, controllers, and automation to streamline infrastructure services.
• Integrate and manage GPU resources within Kubernetes, including device allocation, partitioning, and workload sharing.
• Improve workload scheduling, placement, and resource utilization through Kubernetes scheduling capabilities and complementary workload schedulers.
• Partner with platform engineering, machine learning, HPC, and DevOps teams to support high-throughput, multi-tenant environments.
• Build and maintain observability, monitoring, and telemetry solutions for cluster infrastructure and accelerated workloads.
• Implement secure multi-tenant environments using Kubernetes access controls, namespace isolation, and policy enforcement.
• Maintain infrastructure delivery pipelines using modern GitOps and continuous deployment practices.
• Manage infrastructure as code and Kubernetes configuration using tools such as Terraform and Helm.
• Participate in capacity planning, performance optimization, production readiness, troubleshooting, and incident response.