Staff SRE, AI Infrastructure

Before the detail, here's the challenge you'd help us solve.

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.

Here’s what this particular role covers.

🛠️ About our AI Infrastructure Teams

Our AI Infrastructure teams build and operate the platforms that power Wayve’s AI development. Working across AI Platform, Compute & Data Platform, and Cloud Infrastructure, we provide reliable access to large-scale GPU compute, Kubernetes, storage, and deployment systems. As our GPU fleet and data footprint grow rapidly, you’ll help establish the reliability standards, automation, and operating practices needed to support that scale.⁠

🧠 Your day-to-day

You’ll work hands-on with engineers across our infrastructure teams to identify reliability risks and turn recurring operational problems into durable engineering solutions. You’ll improve observability, automation, deployment safety, capacity planning, and incident learning while helping teams adopt effective SLOs and production-readiness practices. You’ll also troubleshoot complex failures spanning compute, networking, storage, and distributed workloads.

🧩 What you’ll be working on

You’ll improve GPU node health detection and automated recovery, strengthen the resilience of distributed AI training, and develop continuous GitOps delivery using platforms such as Argo CD or Flux. You’ll enhance Kubernetes scheduling, autoscaling, policy enforcement, and resource efficiency; build forecasting for GPU and storage capacity; and create reusable self-service capabilities that help platform teams operate reliably at scale.

🙌 You should apply if

You have hands-on experience owning the reliability of large-scale cloud, Kubernetes, or distributed infrastructure and have recently coded, automated, configured, or troubleshot production systems yourself. You’re comfortable working in Python or Go, infrastructure as code, CI/CD or GitOps, and modern observability practices. You understand distributed-systems failure modes across compute, networking, and storage, can demonstrate measurable improvements to reliability, performance, capacity, or cost, and collaborate effectively across teams. Direct experience with GPU, ML-training, or HPC infrastructure is valuable, but strong experience solving comparable large-scale platform challenges is also relevant.

🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.

More about Wayve:

🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.

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