Member of Technical Staff, Sandbox Infrastructure

📋 Job Overview

At SF Tensor, we're building the future of high-performance compute. We firmly believe that the future of AI depends on rethinking and rebuilding the stack, from hardware to compiler to cloud. We're here to make compute faster, cheaper, and more available. We're building our Kernel Optimizer and Model Foundry to achieve this. We're backed by Susa Ventures, Y Combinator, and other great funds and angels.

🏢 About SF Tensor

We build the fastest GPU compiler in the world. Our approach allows us to search a far wider space while still guaranteeing correctness. We hold #1 on NVIDIA's own kernel benchmark across hundreds of production kernels. We're looking for researchers, engineers, and organizations who agree with the basic premise: you don't get the next leap in AI without a leap in compute first.

🎯 The Role

We're hiring a Member of Technical Staff for Sandbox Infrastructure to build a serverless GPU container service across NVIDIA, AMD, TPU, and Trainium. This service needs to run our compiler, post-training runs, and customer workloads that require isolation. The work now is depth and breadth, adding support for more vendors, higher fidelity instrumentation, faster cold starts, and more features.

✅ Key Responsibilities

• Extend our sandboxing stack to new vendors and accelerators
• Build and maintain GPU virtualization below the runtime, including gVisor work at the driver and ioctl level
• Make sandboxes first-class citizens on spot capacity, which means preemption-aware scheduling, checkpointing, and rescheduling
• Support multi-GPU and multi-node sandboxes, including the interconnect (NVLink, NVSwitch) and RDMA paths (InfiniBand, RoCE) paths those require
• Own live migration end-to-end, including our socket-preserving migration
• Guarantee measurement and profiling fidelity as well as their isolation
• Work directly with the compiler, post-training, and kernel teams to ensure their throughput is not capped by sandboxes

📌 Required Qualifications

• Strong low-level systems engineering background: Linux kernel internals, containers, namespaces, cgroups, syscall interception, or hypervisors
• Experience in GPU systems engineering: drivers, runtimes, or scheduling on accelerator fleets
• Comfortable with distributed systems failure modes: preemption, partial failure, checkpoint/restore, and dealing with states you can't afford to lose
• Proficient in Go, C/C++, or Rust
• Strong bias toward building the thing yourself when no vendor supports what you need

⭐ Desirable Experience

• Worked directly with gVisor, Firecracker, Kata, QEMU/KVM, or similar
• Worked directly on CRIU, live migration, or connection-preserving failover work
• Familiar with NCCL/RCCL, RDMA, InfiniBand, or vendor interconnects
• Run large fleets on spot or other preemptible capacity
• Familiar with bare-metal provisioning, hypervisors, or fleet management at scale
• Security background in isolation boundaries and untrusted code execution

🎁 Benefits

Salary: $275K – $315K • Offers Equity

🛂 Visa & Eligibility

We believe that hard problems get solved in person and most of our work happens at our office in San Francisco.