# Head of Global Compute Capacity & Platform Strategy at Luma AI

- Company: Luma AI
- Role group: Research & AI
- Location: Redwood City
- Type: FullTime
- Remote: yes
- Posted: 2026-07-24
- Status: active
- Apply: https://jobs.ashbyhq.com/lumaai/968808de-1a40-4414-8252-375fd802ce9f?ref=companies-hiring.click

## Description

You'll own Luma's global compute footprint end to end — capacity strategy, multi-million-dollar capital allocation, and systems architecture — making sure research and robotics teams have the runway to ship frontier world models. As a member of the executive team, you're the single person turning capital into capability.

The role spans macro capacity strategy, vendor negotiation, and top-tier systems architecture, and it directs the platform org. It fits a leader who's operated 10k+ accelerator environments and is fluent in both cluster topology and the economics of training. If you're looking for a purely technical or purely strategic seat, this is deliberately both.

What You'll Own

 - Architect multi-year compute strategy: capacity planning, global vendor and cloud partnerships, on-prem vs cloud mix, accelerator supply-chain roadmaps, and custom-silicon evaluation.

 - Provide strategic leadership to infrastructure, distributed systems, and datacenter operations teams.

 - Maximize fleet utilization, targeting more than 50% Model Flops Utilization on flagship training runs.

 - Negotiate, secure, and operate the largest-scale capital deployments, partnering with Finance on unit economics and risk.

 - Unify global capacity so world-model training, simulation, and on-robot inference share a single elastic fleet.

 - Act as the principal executive interface to NVIDIA, AMD, hyperscalers, and frontier silicon vendors.

First 90 Days

One way the first 90 could unfold.

 - Days 1–30 — Immerse & Diagnose: Learn the current fleet, contracts, economics, and utilization gaps.

 - Days 30–60 — Ship & Validate: Land a capacity or utilization decision that improves runway or unit economics.

 - Days 60–90 — Scale & Systemize: Set the multi-year compute roadmap and the platform-org structure to deliver it.

What You Bring

 - 10+ years of engineering leadership in large-scale distributed systems, infrastructure, or technical supply chain, with a track record leading compute platform strategy at a frontier AI lab, hyperscaler, or major autonomy program.

 - Deep technical and commercial fluency in cluster topology, high-speed interconnects (InfiniBand/RoCE), large-scale data systems, and the economics of distributed training.

 - Direct operational oversight of 10k+ accelerator environments in production.

Nice to Have

 - Experience orchestrating capital or infrastructure for training runs at the 100B-parameter or 100k-GPU-day scale.

 - Familiarity with the capacity and latency demands of edge-to-cloud inference and real-time autonomous systems.

About Luma: Luma's mission is to build unified general intelligence that can generate, understand, and operate in the physical world. We believe multimodality is critical for intelligence — the next step beyond language models comes from vision. Luma is an equal opportunity employer.
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