General Compute is the neocloud for alternative chips. Inference is fragmenting: purpose-built silicon from SambaNova, Cerebras, Positron, d-Matrix, and others already beats GPUs on decode, and we productionize that hardware — we buy the racks, find the data center space, and run it for our customers. Each piece of hardware runs the workload it's actually built for: prefill stays on GPUs, decode moves to the chip built for it, and today that means generating tokens 5–7× faster than existing GPU-based competitors. Our customers are frontier labs, fast-growing AI application companies, and asset-light clouds. We closed a $15M seed round in May 2026, and have since closed a $400M debt facility — $100M funded upfront by Upper90, with the balance available for drawdown — collateralized by our inference chips. You will design and build the network our inference fleet runs on. Every rack we buy has to be racked, cabled, connected, and turned into capacity the platform can use. The network is what makes that happen. There's no existing network team, no inherited topology, and no reference architecture to copy. You'll build it right the first time, knowing it has to scale site after site. The problem is also new. The fleet is heterogeneous by design. GPUs handle prefill, and decode runs on accelerators from several ASIC vendors, each with its own interconnect requirements and management tooling. You'll define how those systems connect to each other, to our customers, and to the internet. You'll do it as part of the Data Center Deployment team that stands up every new site.
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Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed