Head of Global Compute Capacity & Platform Strategy
Hybrid (SF Bay Area)$250k - $450kFull-timePosted 3mo ago
About the role
Role responsible for Luma’s global compute footprint end-to-end, bridging capacity strategy, capital allocation, and systems architecture to enable frontier world-model research and robotics development. Executive leadership position overseeing compute platform strategy, infrastructure, and partnerships with vendors and hyperscalers.
Responsibilities
- Architect Multi-Year Compute Strategy: Lead capacity planning, global vendor and cloud partnerships, on-prem vs. cloud mix, and accelerator supply chain roadmaps (H/B-series GPUs, custom silicon evaluation).
- Direct the Platform Org: Provide strategic leadership to our infrastructure, distributed systems, and datacenter operations teams—scaling the organization to support next-generation compute demands.
- Maximize Fleet Utilization: Oversee the architectural efficiency of our cluster configurations to deliver >50% Model Flops Utilization (MFU) on flagship training runs.
- Command a Megawatt Budget: Negotiate, secure, and operate our largest-scale capital deployments for compute infrastructure, partnering directly with Finance to optimize unit economics and risk management.
- Unify Global Capacity: Champion the platform strategy that enables world-model training, heavy simulation rollouts, and real-time on-robot inference to seamlessly share a single, elastic fleet.
- Act as Principal Executive Interface: Serve as the primary commercial and strategic bridge to NVIDIA, AMD, hyperscalers, and frontier silicon vendors.
Qualifications
- 10+ years of engineering leadership experience in large-scale distributed systems, infrastructure, or technical supply chain, with a proven track record of leading compute platform strategy at a frontier AI lab, hyperscaler, or major autonomy program.
- Deep technical & commercial fluency in high-performance cluster topology, high-speed interconnects (InfiniBand/RoCE), large-scale data systems, and the economics of distributed training architectures.
- Direct operational oversight of 10k+ accelerator environments in high-performance production settings.
Skills
Required:Compute strategy and capacity planningHigh-performance cluster architecturesCapital planning and vendor managementOperations leadership of large accelerator environments
Last updated Jul 15, 2026. Interested? Apply on the company site.
About Luma AI
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