We're using LLMs to build neural optimizers, neural scheduling systems, and neural workload tuners. (If you're ex-Google, you can think of it like Borg powered by LLMs.)
Today we use ML to make data warehouses and spark jobs more efficient. We're hiring staff ML engineers to train models that can understand how much compute a job needs, how it scales to larger machines, whether a machine can run more jobs, and so on; and staff infra engineers to take those models and deploy them on real-world production systems.
If this sounds cool, please email me: ben [at] espresso [dot] ai
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