GPU Kernel Engineer
You’d work at the bottom of the stack, writing and tuning the code that runs directly on the GPU: getting more work per second and per dollar out of the hardware, shrinking models so they’re cheaper to run without making them worse, and hunting down the many boring reasons a GPU sits idle. We don’t require GPU or CUDA experience. We’d rather have an excellent low-level systems engineer with no GPU background than an average CUDA programmer.
What we need to see:
Five or more years of low-level performance work where the speed of the system mattered: operating systems, drivers, databases, compilers, trading systems, inference engines.
Strong C or C++ and real comfort at a low level: memory, concurrency, caches, hardware behavior.
A track record of making something significantly faster, where you can explain exactly why it was slow and what you changed. This matters more than anything else on this list.
The habit of measuring. You profile before and after, and you distrust numbers from a sloppy test setup.
Nice to have: operating system, hypervisor, driver, firmware or real-time work; performance tools you built for other engineers; compiler work; actual GPU experience, in industry or open source. We can teach you the GPU. We can’t teach performance instincts.
Working here
San Francisco, in person, five days a week, because the hard problems get solved at a whiteboard. This is a senior role, with competitive compensation plus equity.