Kubernetes Platform Engineer, Data & ML

Plus 2; Santa Clara (CA); On-site; USD 150,000 - 200,000; Full time

Job summary

Plus 2 is seeking a Software Engineer or Senior Software Engineer to fortify our Kubernetes-centric platform. You’ll drive reliability and efficiency of clusters, simplify workload onboarding with self-service patterns, and build reusable batch/workflow capabilities for petabyte-scale processing.

We value strong fundamentals, ownership, and the ability to learn across adjacent areas such as distributed data processing and ML/GPU infra. Elevate platform capabilities with a modern, scalable stack.

Qualifications

• BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.
• Hands‑on experience operating production Kubernetes clusters and GitOps.
• Experience with GPU or ML workload scheduling, queues and multi-tenant resource management.

Responsibilities

• Operate and evolve production Kubernetes clusters including provisioning, control planes, node lifecycle, and storage.
• Build GitOps-based delivery for platform services and user apps using Argo CD, Helm, and Kustomize.
• Develop shared multi-tenant platform capabilities for scheduling, isolation, storage, networking, access control, and observability.
• Build reusable distributed batch and workflow platforms for Spark data processing and GPU-based replay and simulation.
• Ensure compliance with Quality Management System (QMS) requirements and contribute to continuous improvement.

Skills

Kubernetes

Platform engineering

Distributed data processing

ML/GPU infra

Multi-tenant compute

GitOps

Scheduling

Resource isolation

Observability

Ownership

Education

BS/MS/PhD in CS or related

Tools

Argo CD

Helm

Kustomize

Ray

Kubeflow

Apache Spark

Delta Lake

Apache Iceberg

Job description

Plus 2 is seeking a Software Engineer or Senior Software Engineer to fortify our Kubernetes-centric platform. You’ll drive reliability and efficiency of clusters, simplify workload onboarding with self-service patterns, and build reusable batch/workflow capabilities for petabyte-scale processing.

We value strong fundamentals, ownership, and the ability to learn across adjacent areas such as distributed data processing and ML/GPU infra. Elevate platform capabilities with a modern, scalable stack.