Senior Software Engineer, Sandboxes & Virtualization

CoreWeave•Sunnyvale, CA

4d•$139,000 - $242,000•Hybrid

About The Position

About the Team The team is responsible for building and operating secure, high-performance runtime environments that power multi-tenant Kubernetes platforms at scale. We sit at the intersection of container runtimes, lightweight virtualization, GPU infrastructure, and Linux systems engineering. Our mission is to deliver robust, isolated, and efficient execution environments for GPU-accelerated and AI-driven workloads, partnering closely with security, platform, and GPU infrastructure teams to define and implement best-in-class isolation and performance standards. About the Role: In this role, you will design, build, and evolve secure sandboxed runtime environments for workloads running on Kubernetes, with a strong emphasis on runtime isolation, performance, and security. You will develop platforms that integrate container runtimes, lightweight virtual machines, and virtualization technologies, while engineering support for GPU-accelerated workloads in multi-tenant environments. Day-to-day, you’ll design GPU-aware sandboxing and scheduling strategies, optimize containerization and I/O performance for latency-sensitive workloads, and build systems capable of safely executing untrusted or shared GPU workloads. You’ll also contribute to architectural decisions across Linux internals, container runtimes, virtualization layers, and GPU drivers to ensure long-term scalability and operational excellence.

Requirements

3+ years of experience in systems, platform, infrastructure, or production engineering roles building and operating software at scale.
Strong hands-on experience with Kubernetes, container orchestration, and cloud-native architectures, including building Kubernetes-native components (e.g., controllers, operators, or scheduling extensions).
Demonstrated experience designing, implementing, or operating secure execution environments such as container runtimes, sandboxed workloads, or virtualized systems.
Practical experience with lightweight virtualization and sandboxing technologies (e.g., Kata Containers, gVisor, KubeVirt, QEMU, or similar).
Experience supporting or optimizing GPU-accelerated workloads in multi-tenant environments, including knowledge of GPU scheduling, isolation, device passthrough, mediated devices, or GPU virtualization concepts.
Proficiency in systems-oriented programming (Go, C/C++, Rust, or Bash) with a strong understanding of Linux internals and operating system behavior.
Experience diagnosing and resolving complex performance, reliability, or isolation issues across containers, virtual machines, and underlying infrastructure.
Experience conducting profiling, benchmarking, and performance tuning across runtime, virtualization, and GPU stacks.

Nice To Haves

Experience building systems for safely executing untrusted or sensitive workloads in shared environments.
Familiarity with GPU drivers and low-level virtualization or I/O optimization techniques.
Experience defining threat models and implementing runtime security policies in multi-tenant systems.

Responsibilities

design GPU-aware sandboxing and scheduling strategies
optimize containerization and I/O performance for latency-sensitive workloads
build systems capable of safely executing untrusted or shared GPU workloads
contribute to architectural decisions across Linux internals, container runtimes, virtualization layers, and GPU drivers to ensure long-term scalability and operational excellence