Head of Global Compute Capacity & Platform Strategy

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Lead the global compute footprint end-to-end for Luma, shaping capacity strategy, capital allocation, and systems architecture to enable frontier robotics models. Oversee platform and data-center operations, optimize fleet utilization and unit economics, and coordinate with NVIDIA, AMD, and hyperscalers to scale a single elastic compute platform across on-prem and cloud environments.

Location: Redwood City

Workplace: Hybrid

Employment Type: Full time

Job Function: Strategy & Corporate Development

Key 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.

Pay and Benefits

Salary: USD 250,000 - 450,000 annually

Key Requirements

•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.
•Scale Credentials: Experience orchestrating capital or infrastructure for training runs at the >100B-parameter or >100k-GPU-day scale.
•Robotics/Autonomy Context: Familiarity with the unique capacity and latency demands of edge-to-cloud inference and real-time autonomous systems.

Experience:Artificial intelligenceRoboticsHigh-performance computingCloud & data centers

Skills:InfiniBandRoCEGPUDistributed trainingData centersCloudOn-premSiliconNVIDIAAMDHyperscalers

Tech Stack:H/B-series GPUsInfiniBandRoCECloud partnershipsOn-prem vs cloudData systemsCapac ity planningAutomation

Company Brief

Luma

Develops AI-powered tools for capturing, editing, and rendering high-quality 3D scenes from photos and videos, enabling creators to generate photorealistic 3D assets and spatial experiences.

Industry: AR/VR & Spatial Computing

Website

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Luma

1 month ago

Head of Global Compute Capacity & Platform Strategy

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Redwood City

Workplace: Hybrid

Employment Type: Full time

Job Function: Strategy & Corporate Development

Key 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.

Pay and Benefits

Salary: USD 250,000 - 450,000 annually

Key Requirements

•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.
•Scale Credentials: Experience orchestrating capital or infrastructure for training runs at the >100B-parameter or >100k-GPU-day scale.
•Robotics/Autonomy Context: Familiarity with the unique capacity and latency demands of edge-to-cloud inference and real-time autonomous systems.

Experience:Artificial intelligenceRoboticsHigh-performance computingCloud & data centers

Skills:InfiniBandRoCEGPUDistributed trainingData centersCloudOn-premSiliconNVIDIAAMDHyperscalers

Tech Stack:H/B-series GPUsInfiniBandRoCECloud partnershipsOn-prem vs cloudData systemsCapac ity planningAutomation

Company Brief

Luma

Develops AI-powered tools for capturing, editing, and rendering high-quality 3D scenes from photos and videos, enabling creators to generate photorealistic 3D assets and spatial experiences.

Industry: AR/VR & Spatial Computing

Website