Software Engineer/Senior Software Engineer, Data & ML Platform

PlusAI, Inc.; Santa Clara (CA); Hybrid; USD 160,000 - 210,000; Full time

Job summary

PlusAI, Inc. is seeking a Software Engineer (SE) or Senior SE to own data and ML platform workloads on a Kubernetes-backed infrastructure.

You will optimize reliability, efficiency, and self-serve onboarding for large-scale processing, batch workflows, and GPU-accelerated tasks. You will work across scheduling, resource isolation, storage, and observability, building reusable multi-tenant capabilities and end-to-end pipelines with Argo/ Spark integrations.

Qualifications

• BS, MS or PhD in Computer Science or related field, or equivalent practical experience.
• Hands-on experience operating production Kubernetes clusters — node lifecycle, upgrades, troubleshooting.
• 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: eager to take responsibility and drive projects forward end to end.

Responsibilities

• Operate and evolve production Kubernetes clusters end to end.
• Build safe, repeatable GitOps-based delivery for platform services and applications.
• Develop multi-tenant platform capabilities for scheduling, isolation, storage, networking, and observability.
• Build reusable distributed batch/workflow platforms for Spark data processing and GPU-based replay and simulation.
• Ensure work aligns with the company’s QMS requirements and drive continuous improvement.

Skills

Kubernetes

GitOps

Infra-as-code

GPU scheduling

Multi-tenant compute

Ownership

Education

BS/MS/PhD in CS

Tools

Argo CD

Helm

Kustomize

Argo Workflows

Ray

Kubeflow

Delta Lake

Apache Iceberg

Apache Spark

Job description

Software Engineer (SE / Sr SE), Data & ML Platform

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.

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