Senior Systems Engineer Secure Sandbox for Kubernetes GPU

CoreWeave; New York (NY); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Company-paid Life Insurance

Voluntary Supplemental Life Insurance

Short-term Disability Insurance

Long-term Disability Insurance

Flexible Spending Account

Health Savings Account

Tuition Reimbursement

Employee Stock Purchase Program (ESPP)

Mental Wellness Benefits

Family-Forming Support

Paid Parental Leave

Childcare Support

401(k) with Employer Match

Flexible PTO

Catered Lunch

Job summary

CoreWeave is seeking a systems/infrastructure engineer to design and implement secure, high-performance sandboxed runtimes for multi-tenant Kubernetes platforms. You will optimize GPU workloads and influence architecture across Linux internals and virtualization layers.

The role requires 3+ years in systems or infrastructure engineering with expertise in Kubernetes and languages such as Go, C++, or Rust, plus practical virtualization and GPU workload experience.

Qualifications

• Requires 3+ years of experience in systems or infrastructure engineering with strong proficiency in Kubernetes and systems programming languages like Go, C++, or Rust.
• Experience with lightweight virtualization and GPU-accelerated workloads in multi-tenant environments is required.

Responsibilities

• Design and implement secure, high-performance sandboxed runtime environments for multi-tenant Kubernetes platforms.
• Optimize GPU-accelerated workloads and influence architectural decisions across Linux internals and virtualization layers.

Skills

Kubernetes

Container Runtimes

GPU Infrastructure

Linux Systems Engineering

Virtualization

Go

C/C++

Rust

Bash

Kata Containers

gVisor

KubeVirt

QEMU

GPU Scheduling

Performance Tuning

Sandboxing

Job description

CoreWeave is seeking a systems/infrastructure engineer to design and implement secure, high-performance sandboxed runtimes for multi-tenant Kubernetes platforms. You will optimize GPU workloads and influence architecture across Linux internals and virtualization layers.

The role requires 3+ years in systems or infrastructure engineering with expertise in Kubernetes and languages such as Go, C++, or Rust, plus practical virtualization and GPU workload experience.