Wafer, San Francisco
Inference performance depends on how efficiently models use the underlying hardware. Techniques across kernels, compilers, runtimes, and serving systems can dramatically improve latency and throughput, but these optimizations are difficult, hardware-specific, and slow to reproduce across new accelerators. And none of it counts until it is running in a customer's production traffic.
At Wafer, we are building AI systems that automatically optimize inference workloads across silicon. The goal is fungible token capacity. Any accelerator optimized toward serving inference most efficiently.
Wafer is well funded and serves trillions of tokens a month for mission critical workloads. We serve the highest performance inference to fast-growing AI startups.
Members of Technical Staff build the systems that make that possible: the kernels, runtimes, agents and infrastructure behind every workload we serve. Our forward deployed engineers run customer deployments day to day and bring you in on the hardest problems.
On-site in San Francisco, five days a week. Small team with massive surface area and ownership. You operate with complete autonomy of how to solve problems. We don't see engineers as code writers, but as problem solvers. You will work across the stack to build a company scaling extremely quickly.
This is not a role that lives in meetings. Nearly all of your time is engineering. What makes it different is who that engineering is for: you are responsible for a named set of customers, their workloads run on what you build, and you are the person they hear from when it matters.
IncoBay Area HQ +1
$200K–$350K / yr
Posted Jul 22, 2026
$175K–$275K / yr
Posted Sep 17, 2026
Gimlet LabsSan Francisco, CA
$150K–$390K / yr
Posted Mar 10, 2026
$225K–$275K / yr
Posted Aug 29, 2026
$200K–$350K / yr
Posted Jul 22, 2026
Gimlet LabsSan Francisco, CA
$150K–$390K / yr
Posted 19 days ago
Source: the Wafer Ashby job board. We last checked this job 9 h ago. We first saw it 8 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.
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This base pay is near the median for inference and ML systems jobs in the Bay Area with no level in the job title.
We compare the middle of each posted range. This is base pay as posted. The group does not include this job.