Lead GPU Sandbox & Virtualization Engineer

SF Tensor; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Relocation to SF

Job summary

SF Tensor is seeking a highly capable systems engineer to own a serverless GPU container service spanning NVIDIA, AMD, TPU and Trainium. You will extend sandboxing across vendors, implement GPU virtualization, and ensure isolation fidelity for live workloads.

Candidates should have a strong background in Linux kernel, containers, and hypervisors, plus experience with GPU systems, preemption handling, and cross-node sandboxes. Relocation to San Francisco is offered.

Qualifications

• A strong background in low level systems with Linux kernel, containers, namespaces and cgroups.
• Experience with GPU systems, drivers, runtimes or accelerator fleet scheduling.
• Familiarity with distributed failure modes such as preemption, partial failure, checkpoint and restore.
• Fluency in Go, C/C++ or Rust; ability to build missing tools when vendors don’t provide them.

Responsibilities

• Extend the sandboxing stack to new vendors and accelerators.
• Build and maintain GPU virtualization, including gVisor work at driver and ioctl level.
• Ensure sandboxes survive spot capacity with preemption-aware scheduling, checkpointing and rescheduling.
• Support multi-GPU and multi-node sandboxes across NVLink, NVSwitch, InfiniBand and RoCE.
• Own live migration, including socket-preserving migration.
• Guarantee measurement and profiling fidelity under isolation.
• Keep the compiler, post-training and kernel teams from being throughput-limited by sandboxes.

Skills

Low-level systems

Linux kernel

Containers

Namespaces

cgroups

syscall interception

Hypervisors

GPU systems experience

Distributed failure handling

Go

C/C++

Rust

Tools

gVisor

QEMU/KVM

Kata

Job description

SF Tensor is seeking a highly capable systems engineer to own a serverless GPU container service spanning NVIDIA, AMD, TPU and Trainium. You will extend sandboxing across vendors, implement GPU virtualization, and ensure isolation fidelity for live workloads.

Candidates should have a strong background in Linux kernel, containers, and hypervisors, plus experience with GPU systems, preemption handling, and cross-node sandboxes. Relocation to San Francisco is offered.