Staff Cloud Hypervisor Engineer, ComputePosted today$215K–$260K

The opportunity

Crusoe is on a mission to accelerate the abundance of energy and intelligence . As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads.

What you'll do

  • Next-Gen Hypervisor Architecture: Lead the R&D and implementation of core hypervisor components (KVM, QEMU, or custom Rust-based solutions) specifically optimized for massive-scale GPU fleets.

  • AI Hardware Virtualization: Develop and refine advanced hardware pass-through and abstraction techniques (SR-IOV, VFIO, mdev) to ensure NVIDIA GPUs and BlueField DPUs operate with near-zero latency in a multi-tenant environment.

  • The "Holy Grail" Challenges: Solve high-stakes technical hurdles such as live migration for AI workloads with 80GB+ VRAM and optimizing PCIe peer-to-peer communication between virtualized accelerators.

  • Performance Research & Profiling: Conduct deep-dive bottleneck analysis across the entire stack—from CPU microarchitecture and MMU virtualization to guest OS scheduling—to minimize jitter and maximize throughput.

  • Open Source Leadership: Actively contribute to and maintain upstream open-source virtualization projects, positioning Crusoe as a thought leader in the Linux kernel and virtualization communities.

  • Security & Isolation: Architect robust security boundaries for AI-native cloud infrastructure, balancing high-performance hardware access with strict multi-tenant isolation and hardening.

What they're looking for

  • + Years of Experience: Proven track record in hypervisor internals, kernel development, or low-level systems programming.
  • Deep Virtualization Expertise: Expert-level knowledge of CPU virtualization (Intel VT-x, AMD-V) and memory virtualization (EPT/NPT, HugePages). You should be comfortable discussing the nuances of VMExit overhead.
  • Hardware-Software Integration: Experience working with specialized AI hardware, including GPUs, InfiniBand/RoCE NICs, and SmartNICs/DPUs.
  • Programming & Tooling: Mastery of C and C++ is required; proficiency in Rust for modern systems programming is highly preferred. Experience with QEMU, KVM, and Linux kernel debugging tools (perf, ftrace, eBPF).