GPU & Runtime Systems Engineer: Secure Kubernetes Sandboxes

Coreweave; Livingston (NJ); On-site; USD 182,000 - 242,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Life Insurance

Disability insurance

401(k) with employer match

Flexible PTO

Catered lunch

Casual work environment

ESPP stock program

Job summary

CoreWeave is hiring a GPU & Runtime Systems Engineer to design, build, and evolve secure sandboxed runtime environments for Kubernetes workloads. You will integrate container runtimes, lightweight VMs, and virtualization technologies to support GPU-accelerated workloads in multi-tenant environments.

Day-to-day, you'll develop GPU-aware sandboxing and scheduling strategies, optimize containerization and I/O performance for latency-sensitive workloads, and influence architectural decisions across

Qualifications

• Strong hands-on experience with Kubernetes and cloud-native architectures.
• Experience designing, implementing, or operating secure execution environments (container runtimes, sandboxed workloads, or virtualized systems).
• Proficient in Linux internals and systems programming.

Responsibilities

• Design secure execution environments for containerized and virtualized workloads.
• Build GPU-aware scheduling, isolation, and resource management for multi-tenant workloads.
• Optimize container, VM, and I/O performance across GPU-accelerated workloads.
• Conduct profiling, benchmarking, and performance tuning for runtime, virtualization, and GPU stacks.
• Contribute to architectural decisions across Linux internals, container runtimes, virtualization layers, and GPU drivers.
• Collaborate with security, platform, and infrastructure teams to define runtime isolation and performance standards.

Skills

Kubernetes

Go programming

Linux systems

GPU stacks

Tools

Kata Containers

gVisor

KubeVirt

QEMU

Job description

CoreWeave is hiring a GPU & Runtime Systems Engineer to design, build, and evolve secure sandboxed runtime environments for Kubernetes workloads. You will integrate container runtimes, lightweight VMs, and virtualization technologies to support GPU-accelerated workloads in multi-tenant environments.

Day-to-day, you'll develop GPU-aware sandboxing and scheduling strategies, optimize containerization and I/O performance for latency-sensitive workloads, and influence architectural decisions across