General Compute

United States
8 Total Employees
Year Founded: 2026

Jobs at General Compute

Let Your Resume Do The Work
Upload your resume to be matched with jobs you're a great fit for.

18 Hours AgoSaved
Hybrid
2 Locations
Artificial Intelligence • Cloud • Semiconductor • Infrastructure as a Service (IaaS)
Build the foundational inference cloud platform, including its control plane, API, serving layer, routing, model placement, scheduling, reliability, and observability. The role involves scaling a heterogeneous GPU and ASIC fleet, partnering with data center and model deployment teams, and shaping platform architecture as an early individual contributor at a small startup.
18 Hours AgoSaved
Hybrid
2 Locations
Artificial Intelligence • Cloud • Semiconductor • Infrastructure as a Service (IaaS)
Own the end-to-end LLM inference serving stack for specialized ASIC hardware. Design request routing, batching, scheduling, KV-cache management, autoscaling, monitoring, alerting, and failover. Optimize throughput and cost per token, support production reliability and on-call operations, collaborate with compiler and hardware bring-up teams, shape the serving roadmap, and establish technical standards for a growing engineering team.
18 Hours AgoSaved
Hybrid
San Francisco, CA, USA
Artificial Intelligence • Cloud • Semiconductor • Infrastructure as a Service (IaaS)
Own General Compute’s capital markets strategy, including structuring and closing asset-backed financing facilities, managing lender relationships, and developing the company’s credit story. Build financial models, lead data rooms and lender processes, manage subsequent debt tranches and customer contract financing, and oversee day-to-day company finance, cash flow, budgeting, and bookkeeping. This is the first dedicated capital markets role and reports directly to the CEO.
18 Hours AgoSaved
Hybrid
San Francisco, CA, USA
Artificial Intelligence • Cloud • Semiconductor • Infrastructure as a Service (IaaS)
Own the infrastructure layer of an AI inference cloud, including the Kubernetes-based control plane, gateway, load balancing, observability, capacity planning, accelerator operations, and incident response. The role begins hands-on and expands to building and managing the infrastructure team. Responsibilities include supporting heterogeneous ASIC and GPU fleets, partnering with hardware vendors, optimizing tail latency, establishing on-call practices, and bringing up new hardware platforms.