San Francisco Compute Co.
Supercomputing Engineer
San Francisco Compute Co., San Francisco, California, United States, 94199
We're building the company which will de-risk the largest infrastructure build-out in history.
When people finance GPU clusters, the datacenters housing them, and the infrastructure powering them, they need "offtake" - meaning someone has signed a contract to lease the cluster for a period of time before its even built.
Financing a GPU cluster is inherently risky, since margins are thin and volumes are huge. Lenders don't want to take on the risk that cluster developers can't repay their loan, and cluster developers really don't want to risk not selling their cluster. As a result, risk is offloaded to the customer using fixed-price long-term contracts.
If you don't mitigate this customer risk, there's a bubble. This isn't SaaS anymore - application layer companies sign multi-year contracts for computer and inference, but sell to customers on monthly subscriptions. If you mess up a purchase, it's game over: a minor shift in your revenue growth rate might mean the difference between profit or bankruptcy. But what if companies could exit their contract by selling it back to the market?
Otherwise, as AI scales, compute only becomes available to folks who can effectively take on that risk. A 2-person startup in a San Francisco Victorian can't realistically sign a 5-year take or pay contract on $100m supercomputers. But they may be able to buy the month of liquidity that someone else sold back.
So that's what we make: a liquid market for GPU offtake.
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, participating in on-call rotation, 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 deeply understand Linux, networking fundamentals, CUDA, NCCL, and Infiniband
You enjoy automating hardware deployments, leveraging IaC wherever possible
You appreciate and value good documentation
Some Nice to Haves
Experience with Rust (our bare metal tooling is written in Rust)
Experience with Linux virtualization (KVM, QEMU, libvirt, etc.)
Experience with Kubernetes implementation including CRDs and CNIs
Experience with HPC network architectures (eBGP, fat-tree, VXLAN, MCLAG, etc.)
Compensation
US: $170k - $300k + equity
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 hiring@sfcompute.com
#J-18808-Ljbffr
When people finance GPU clusters, the datacenters housing them, and the infrastructure powering them, they need "offtake" - meaning someone has signed a contract to lease the cluster for a period of time before its even built.
Financing a GPU cluster is inherently risky, since margins are thin and volumes are huge. Lenders don't want to take on the risk that cluster developers can't repay their loan, and cluster developers really don't want to risk not selling their cluster. As a result, risk is offloaded to the customer using fixed-price long-term contracts.
If you don't mitigate this customer risk, there's a bubble. This isn't SaaS anymore - application layer companies sign multi-year contracts for computer and inference, but sell to customers on monthly subscriptions. If you mess up a purchase, it's game over: a minor shift in your revenue growth rate might mean the difference between profit or bankruptcy. But what if companies could exit their contract by selling it back to the market?
Otherwise, as AI scales, compute only becomes available to folks who can effectively take on that risk. A 2-person startup in a San Francisco Victorian can't realistically sign a 5-year take or pay contract on $100m supercomputers. But they may be able to buy the month of liquidity that someone else sold back.
So that's what we make: a liquid market for GPU offtake.
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, participating in on-call rotation, 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 deeply understand Linux, networking fundamentals, CUDA, NCCL, and Infiniband
You enjoy automating hardware deployments, leveraging IaC wherever possible
You appreciate and value good documentation
Some Nice to Haves
Experience with Rust (our bare metal tooling is written in Rust)
Experience with Linux virtualization (KVM, QEMU, libvirt, etc.)
Experience with Kubernetes implementation including CRDs and CNIs
Experience with HPC network architectures (eBGP, fat-tree, VXLAN, MCLAG, etc.)
Compensation
US: $170k - $300k + equity
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 hiring@sfcompute.com
#J-18808-Ljbffr