Relace delivers purpose-built AI models and scalable infrastructure for coding agents, offering ultra-fast code retrieval, merging, and autonomous workflows. Cut down errors and accelerate development with Relace. Backed by Y Combinator and a16z.
About the role
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. Found on 1752vc Careers, the job board for startup and VC roles.
More about this role
Relace is building a globally distributed inference cloud. Customers send us requests, we run them on our own GPU fleet around the world, and we compete on price, speed and reliability against companies far larger than us. We have customers and revenue today, we’re venture backed, and the team is still small, so you’ll own whole systems, not slices of them.
We build our own stack, and the fleet runs on Kubernetes across multiple clouds. Performance is the business: ten percent faster is ten percent more revenue. If you like making things fast, this is about as direct as it gets. You can trace a change you shipped this week to what it earned.
Some numbers: we process 800B+ tokens a day, we’ve grown 3x in the last three months, we’re one of the top providers by volume on OpenRouter, and we raised a $23M Series A led by Andreessen Horowitz, with participation from Matrix Partners and Y Combinator.
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....
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