About

Compute is a commodity. We think people should buy it like one.

Startups shouldn’t be forced to buy a year’s worth of compute time in order to get market rate and compute providers shouldn’t go bankrupt because they can’t fully book their clusters.

At SF Compute, our goal is to solve this issue the same way this was solved for every other commodity — by building a venue where compute contracts are traded in real-time and by bringing a new kind of participant into the supply chain, traders.

If we succeed, buyers will be able to get a good price for any order, whether it’s 32 H100s for a month or 8,000 H100s for an hour, and sellers will instantly book out their clusters because traders will speculatively buy them, for a spread. Every FLOP will flow through us somewhere in the supply chain. What Brent is for oil, we will be for compute.

About the Role

ML training clusters are some of the most high performance computers on the planet. Even relatively small clusters would have been in the TOP500 5 years ago. Our supercomputing team is responsible for keeping our compute clusters running smoothly, monitoring hardware health, and fixing things when they go wrong. We believe strongly in automation — code is the only reliable way to manage hardware at scale. As we scale, this will become a more data-driven role, predicting failures before they happen. We’re a small team, so you’ll be spending time talking to customers as well.

About You

• You’ve managed at least one GPU training cluster in the past (ideally a cluster with >1k GPU’s but not required)

• You appreciate and value good documentation

• You have experience provisioning and managing Kubernetes clusters

• You deeply understand Linux, networking fundamentals, CUDA, NCCL, and Infiniband

• You enjoy creating large self-correcting systems that keep hardware humming

• You meet at least two of the nice-to-haves below

Some Nice to Haves

• Experience with Go or Rust (>2 years)

• Experience with distributed storage systems (Weka, VAST, Ceph, etc.)

• Experience with HPC network architectures (eBGP, fat-tree, VXLAN, MCLAG, etc.)

• Experience with Linux virtualization (KVM, QEMU, libvirt, etc.)

• Experience with performance optimization of machine learning kernels

Benefits

Generous equity grant

Team members are offered a competitive salary along with equity in the company

Visa Sponsorships

Yes, we sponsor visas and work permits

Retirement matching

We match 401(k) plans up to 4%

Medical, dental & vision

We offer competitive medical, dental, vision insurance for employees and dependents and cover 100% of premiums

Time off

We offer unlimited paid time off as well as 10+ observed holidays

Parental leave

We offer biological, adoptive, and foster parents paid time off to spend quality time with family

Daily lunch

We cover lunch daily for employees

Unlimited office book budget

You can buy as many books for the office as you want

The San Francisco Compute Company is committed to maintaining a workplace free from discrimination and harassment.

We make employment decisions based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, belief, national origin, social or ethical origin, age, physical, mental, or sensory disability, sexual orientation, gender identity or expression, marital status, civil union or domestic partnership status, past or present military service, HIV status, family medical history or genetic information, family or parental status including pregnancy, or any other status protected by law.

We welcome the opportunity to consider qualified applicants with prior arrest or conviction records. Our commitment to diversity includes hiring talented individuals regardless of their criminal history, in accordance with local, state, and federal laws, including San Francisco’s Fair Chance Ordinance and California’s ban-the-box laws.

If you require reasonable accommodation for any reason, please reach out to us at team@sfcompute.com.