Member of Technical Staff, GPU Kernels at Sf Tensor · LumiJobs

Responsibilities

We build the fastest GPU compiler in the world. Most compilers have to preserve correctness at every transform, constraining how far they can search, while we prove correctness at the end instead, allowing us to search a far wider space, with agents, with RL, with anything that works and still guarantee the result. It's why we hold #1 on NVIDIA's own kernel benchmark across hundreds of production kernels.
We're hiring a Member of Technical Staff for GPU Kernel Engineering to establish and push the envelope on what the hardware can actually do before any search ever runs. To this extent, you'll write and hand-optimize kernels that execute during pre-training, post-training and inference, across NVIDIA, AMD, TPU and Trainium. You'll then take those learnings and convert them into structures the compiler can search: instruction sequences, scheduling strategies, cost signals, to ensure that the ceiling you worked for by hand can become the floor for the search finding kernels everywhere else.
You'll have access to better tooling than anywhere else because we own the stack all the way down to the ISA, allowing us to create kernels that others can't even express. For example, our custom LLVM backend emits cubins directly, without a PTX handoff or ptxas doing our scheduling, letting us write kernels that have no expression in CUDA at all. Our team understands the hardware better than anyone else, to this extent we've built a bit-exact software model of Blackwell's tcgen05.
You'll be writing kernels that ship immediately on runs such as pre-training AlphaFold v3 at 3.4× the throughput, post-training robotics models on Trainium or running our custom RL rollout engine on TPU at multi-100B parameter scale.
You'll write and hand-optimize kernels for real workloads to find the ceiling before the search goes looking for it
You'll profile at the microarchitectural level: SM and CU utilization, warp stalls, memory bank conflicts, register pressure, instruction throughput, occupancy tradeoffs
You'll debug down to the clock behavior, thermal throttling and driver paths where the docs are often missing or just wrong
You'll turn hard-won knowledge into a machine-searchable structure the compiler can explore on it's own
You'll work below PTX at the ISA-level, reasoning about SASS and cubins to emit schedules PTX has no way to express
You'll build the performance models, microbenchmarks and tooling that lets us predict kernel behavior
You'll work alongside the formal correctness team, so that aggressive, unintuitive kernels ship with a formal proof attached
Expect roughly two-thirds of your time on kernels and one-third on turning what you learned into the compiler search space.

Member of Technical Staff, GPU Kernels

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Sf Tensor

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