Software Engineer/Senior Software Engineer (Data & Machine Learning Platform)

PlusAI; Santa Clara (CA); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Unlimited PTO

Flexible working

Health benefits

Equity, 401k and FSA

Professional development

Catered lunches

Job summary

PlusAI is seeking a Software Engineer to strengthen our Kubernetes platform, focusing on reliability, onboarding, and scalable batch/workflow capabilities for petabyte-scale processing.

You will operate production Kubernetes clusters end to end, implement GitOps with Argo CD, Helm, and Kustomize, and collaborate on multi-tenant compute, GPU scheduling, and data-processing pipelines with Spark.

Qualifications

• BS, MS, or PhD in Computer Science or related field, or equivalent practical experience.
• Hands-on experience operating production Kubernetes clusters with node lifecycle, upgrades, troubleshooting, and GitOps and infrastructure-as-code.
• Self-driven with ownership and ability to drive projects end to end.
• Experience with GPU or ML workload scheduling, queueing and priorities, fractional GPU sharing, autoscaling, or multi-tenant resource management.

Responsibilities

• Improve reliability and efficiency of Kubernetes infrastructure.
• Make workload onboarding simpler and more self-service.
• Build reusable batch and workflow capabilities for petabyte-scale processing.
• Operate production Kubernetes clusters end to end including provisioning, control planes, GPUs, networking, and storage.
• Develop GitOps-based delivery using Argo CD, Helm, and Kustomize.
• Create multi-tenant platform capabilities for scheduling, isolation, storage, networking, and observability.
• Build and enhance distributed batch/workflow platforms for Spark processing and GPU replay/simulation.

Skills

Kubernetes

Platform engineering

Distributed data processing

ML/GPU infrastructure

Multi-tenant compute systems

GitOps

Argo CD

Helm

Kustomize

Spark

Ray

Kubeflow

Argo Workflows

Delta Lake

Apache Iceberg

GPU workload scheduling

Autoscaling

Education

BS, MS, or PhD in Computer Science or related field

Tools

Argo CD

Helm

Kustomize

Kubeflow

Argo Workflows

Spark

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
• 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

Benefits

• Unlimited PTO: Unlimited paid time off on top of company holidays to recharge and enjoy as needed
• Flexible working: Flexibile work arrangements and technology to help manage life’s demands at the office and remote
• Health benefits: Tiered options in medical, dental, and vision insurance to fit your unique needs
• Future building: Equity, 401k and FSA options for all eligible employees to help build for your future
• Professional development: Company-sponsored professional development opportunities such as conferences, training, and workshops
• Catered lunches: Daily catered lunches at both of our Santa Clara and Fremont offices

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

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

Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end

Experience with GPU or ML workload scheduling, queueing and priorities, fractional GPU sharing, autoscaling, or multi-tenant resource management

Experience with Ray or Kubeflow

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

Experience with lakehouse technologies such as Delta Lake or Apache Iceberg