Lead Infrastructure and Reliability Engineer (Systems & Scale)

Leads infrastructure reliability for large-scale GPU clusters, architects systems for training/inference scaling, and builds a high-performing engineering team. Requires deep Linux/distributed systems expertise, GPU production experience, and Kubernetes fluency.

About the job

What You’ll Own

Reliability of the Frontier

Architect and operate large, heterogeneous GPU environments under extreme demand
Improve utilization and performance where small gains materially change company outcomes
Resolve failures that span hardware, OS, runtimes, and orchestration
Eliminate entire classes of instability
Build mechanisms that make heroics unnecessary

Scaling Training & Inference

Define how infrastructure and workloads evolve as cluster size and concurrency grow
Design scheduling, placement, and resource management approaches for increasingly complex jobs
Work directly with research to build the systems required for new model capabilities
Ensure inference platforms scale rapidly without sacrificing reliability or latency
Anticipate where today’s abstractions will fail and redesign ahead of them

Building the Organization

Hire and develop exceptional systems and reliability engineers
Set the bar for technical depth, judgment, and production ownership
Shape architecture early through strong partnerships with research and product
Translate reliability constraints into long-term platform strategy

Who You Are

Required:

Deep expertise in Linux and distributed systems
Experience operating GPU / accelerator clusters in real production environments
Strong fluency in Kubernetes and modern open-source infrastructure
Comfortable debugging across hardware → kernel → runtime → orchestration
You understand how systems behave under contention and at scale
You write code and build automation
You think in bottlenecks, failure modes, and tradeoffs
Engineers trust your judgment, especially when things break

Important: This role requires comfort operating close to upstream and close to the metal. If most of your experience has been inside highly abstracted internal platforms where others owned the underlying machinery, this is unlikely to be a match.

Leadership Expectations:

You raise reliability standards across the company
You influence product and research architecture early
You build strong partnerships, not ticket queues
You attract and level up exceptional engineers
You are curious how models use infrastructure, because improving systems expands what becomes possible