Software Engineer/Senior Software Engineer, Data & ML Platform

PlusAI; Santa Clara (CA); On-site; USD 135,000 - 200,000; Full time

Job summary

PlusAI in Santa Clara, CA, is seeking a Software Engineer or Senior Software Engineer to strengthen our Kubernetes infrastructure, simplify workload onboarding, and create reusable batch and workflow capabilities for petabyte-scale processing.

You will work on production clusters, implement GitOps workflows with Argo CD, Helm, and Kustomize, and advance GPU/ML workload scheduling and multi-tenant resource management. A strong foundation in distributed systems is needed.

Qualifications

• Hands-on experience operating production Kubernetes clusters and GitOps/infrastructure-as-code
• Experience with GPU or ML workload scheduling, queueing and priorities, fractional GPU sharing, autoscaling
• Self-driven with ownership and strong learning ability

Responsibilities

• Operate and evolve production Kubernetes clusters end to end (provisioning, control planes, node lifecycle, GPU container runtime)
• Build safe, repeatable GitOps-based delivery for platform services and user apps using Argo CD, Helm, and Kustomize
• Develop multi-tenant platform capabilities for scheduling, isolation, storage, networking, access control, secrets and observability
• Build reusable distributed batch/workflow platforms for Spark processing and GPU-based replay/simulation
• Adhere to QMS requirements and contribute to continuous improvement efforts

Skills

Kubernetes

GitOps

Ownership

GPU scheduling

Education

BS/MS/PhD in CS or related

Tools

Argo CD

Helm

Kustomize

Ray

Kubeflow

Spark

Argo Workflows

Delta Lake

Apache Iceberg

Job description

All key offline workloads — large-scale data processing, simulation, auto-labeling, scenario mining, and model training — run on the compute platform this role owns. In this role, you will improve the reliability and efficiency of our Kubernetes infrastructure, make workload onboarding simpler and more self-service, and build reusable batch and workflow capabilities for petabyte-scale processing. We are looking for strong Kubernetes and platform-engineering fundamentals, depth in at least one adjacent area—distributed data processing, ML/GPU infrastructure, or multi-tenant compute systems—and the curiosity and ownership to grow across the others.

We are open to candidates at either the Software Engineer or Senior Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn.

Responsibilities

• Operate and evolve our production Kubernetes clusters end to end: bare-metal provisioning automation, highly available control planes, node lifecycle, GPU container runtime, networking, and storage
• Build safe, repeatable GitOps-based delivery for platform services and user applications using tools such as Argo CD, Helm, and Kustomize
• Develop shared multi-tenant platform capabilities for scheduling, resource isolation, storage, networking, access control, secrets, and observability while improving CPU/GPU utilization and cost efficiency
• Build and improve reusable distributed batch and workflow platforms for Spark data processing and GPU-based replay and simulation
• Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts

Required Skills

• BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience
• Hands‑on experience operating production Kubernetes clusters — node lifecycle, upgrades, troubleshooting — plus GitOps and infrastructure‑as‑code experience
• Experience with GPU or ML workload scheduling, queueing and priorities, fractional GPU sharing, autoscaling, or multi-tenant resource management
• Self‑driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end

Preferred Skills

• Experience with Ray or Kubeflow
• Experience with lakehouse technologies such as Delta Lake or Apache Iceberg
• Experience operating large-scale distributed data‑processing and workflow systems, with hands‑on depth in a system such as Apache Spark and working knowledge of Argo Workflows or an equivalent orchestrator

$135,000 - $200,000 a year