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. Are you interested in working at SF Compute but don't see the perfect role right now? We still invite you to apply! Please submit your resume using the application link below, and include a brief cover letter letting us know why you would be a great addition to SF Compute. Please note that our team is very small right now and we can only respond to candidates where we see a potential role fit. While we gladly accept applications from everyone, we're especially interested in people who have experience with any of the following: Rust software development Linux systems engineering High Performance Computing (HPC) HPC storage and networking technologies Experience working with clusters with 1000+ GPUs General experience and interest in scaling startups!
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Job Type
Full-time
Education Level
No Education Listed
Number of Employees
11-50 employees