# Staff AI Infrastructure Engineer at Luma AI

- Company: Luma AI
- Role group: Product & Engineering
- Location: Redwood City
- Type: FullTime
- Remote: yes
- Posted: 2026-07-24
- Status: active
- Apply: https://jobs.ashbyhq.com/lumaai/ee0a18bc-8f7a-4c9f-b99b-7c99a37ce529?ref=companies-hiring.click

## Description

You'll own the reliability of Luma's 10k+ GPU fleet: the scheduling, efficiency, and resilience that research and products depend on. As a Staff AI Infrastructure Engineer, you'll be a technical authority who turns deep systems knowledge into repeatable, company-wide reliability, and a leader other strong engineers want to work with.

This is close-to-the-metal work — kernels, containers, schedulers, networking, storage, GPU behavior — under demand hard enough that yesterday's solutions break regularly. It's also a technical-leadership role: you'll set the bar and grow the team. If most of your experience has been inside highly abstracted internal platforms where others owned the underlying machinery, this likely isn't a match.

What You'll Own

 - Architect and operate large, heterogeneous GPU environments under extreme demand, improving utilization and performance where small gains change company outcomes.

 - Resolve failures spanning hardware, OS, runtimes, and orchestration, and eliminate whole classes of instability.

 - Define how infrastructure and workloads evolve as cluster size and concurrency grow — scheduling, placement, resource management.

 - Work directly with research to build the systems new model capabilities require, and scale inference without sacrificing reliability or latency.

 - Hire and develop exceptional systems and reliability engineers, and set the bar for depth, judgment, and production ownership.

 - Shape product and research architecture early through strong partnerships.

First 90 Days

One way the first 90 could unfold.

 - Days 1–30 — Immerse & Diagnose: Learn the fleet, its failure modes, and the biggest reliability and utilization gaps.

 - Days 30–60 — Ship & Validate: Eliminate a recurring class of instability or land a utilization or performance win that moves company outcomes.

 - Days 60–90 — Scale & Systemize: Set the reliability direction, redesign ahead of where today's abstractions will fail, and begin building the team.

What You Bring

 - Deep expertise in Linux and distributed systems.

 - Experience operating GPU or accelerator clusters in real production environments.

 - Strong fluency in Kubernetes and modern open-source infrastructure.

 - Comfort debugging across hardware, kernel, runtime, and orchestration, and understanding how systems behave under contention and at scale.

 - You write code and build automation, and think in bottlenecks, failure modes, and trade-offs.

 - Judgment engineers trust, especially when things break.

Nice to Have

 - You raise reliability standards company-wide and influence product and research architecture early.

 - You build partnerships rather than ticket queues, and attract and level up strong engineers.

 - Curiosity for how models use infrastructure, because improving systems expands what becomes possible.

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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