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About the Role
Build the inference cloud itself, including the control plane, API, and serving layer, transforming racks into a sellable product. Establish reliability as core infrastructure from day one and solve the technical challenge of managing a heterogeneous fleet of GPUs and ASICs for optimal inference performance.
Responsibilities
- Build and own the control plane, including routing, model placement, and scheduling across a mixed ASIC/GPU pool.
- Build the API and serving layer to expose rack capacity as a sellable product.
- Build in reliability and observability from day one.
- Scale the platform ahead of the demand curve.
- Partner closely with data center deployment and model bring-up teams.
- Act as a founding technical voice on platform architecture.
Requirements
- Strong systems engineering background on cloud control planes/serving infra at scale.
- Comfort being a high-impact individual contributor rather than a manager.
- Track record of building reliability from scratch.
- Comfort with hardware heterogeneity and ambiguity.
- Genuine interest in being an early hire at a small company.
Skills
- LLM-serving infra experience (vLLM, TGI, Ray Serve, etc.)
- Experience running non-NVIDIA accelerators (TPUs/ASICs) in production.
About the Company
- General Compute is the neocloud for alternative chips.
- We productionize purpose-built inference hardware from various vendors, buying racks, finding data center space, and running it for customers.
- Our solution offers significantly faster token generation compared to GPU-based competitors.
- Customers include frontier labs, fast-growing AI application companies, and asset-light clouds.
- Closed a $15M seed round in May 2026 and a $400M debt facility.