Jobs at General Compute

Design and own scalable data center networks for a heterogeneous AI inference fleet. Responsibilities include leaf-spine architecture, GPU-to-ASIC connectivity, site deployment, cabling, cross-connects, external connectivity, tenant isolation, automation, monitoring, incident response, and vendor management. The role requires hands-on network design and deployment across high-performance AI/HPC environments and close collaboration with platform engineering.

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.

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.