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Staff SRE, AI Infrastructure

Full-time Hybrid work

Publication date: 02/11/2026

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.

Responsibilities

Work hands-on with engineers across infrastructure teams to identify reliability risks and turn recurring operational problems into durable engineering solutions; Improve observability, automation, deployment safety, capacity planning, and incident learning; Help teams adopt effective SLOs and production-readiness practices; Troubleshoot complex failures spanning compute, networking, storage, and distributed workloads; Improve GPU node health detection and automated recovery; Strengthen the resilience of distributed AI training; Develop continuous GitOps delivery using platforms such as Argo CD or Flux; Enhance Kubernetes scheduling, autoscaling, policy enforcement, and resource efficiency; Build forecasting for GPU and storage capacity; Create reusable self-service capabilities that help platform teams operate reliably at scale

Requirements

Hands-on experience owning the reliability of large-scale cloud, Kubernetes, or distributed infrastructure; Recently coded, automated, configured, or troubleshot production systems; Comfortable working in Python or Go; Experience with infrastructure as code, CI/CD or GitOps, and modern observability practices; Understanding of distributed-systems failure modes across compute, networking, and storage; Can demonstrate measurable improvements to reliability, performance, capacity, or cost; Collaborates effectively across teams

Nice to have

Direct experience with GPU, ML-training, or HPC infrastructure; Strong experience solving comparable large-scale platform challenges

Benefits

Salaries benchmarked against the market annually; Meaningful equity; Relocation support and visa sponsorship where applicable; Hybrid working, core hours, and hands-on work in vehicle workshops and labs; Learning and development budgets for training, conferences and growth; Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, and team socials
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