Senior 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.
The role
As a Cloud Site Reliability Engineer at Wayve, you will build and scale the reliability foundations of our AI cloud platform. This includes our Model Development Platform (powering end-to-end model development from raw data to on-road experimentation) and our GPU Compute platform (large-scale, multi-tenant GPU fleets and scheduling systems driving model training and inference at scale).
This is a founding Cloud SRE role. You won’t inherit a mature SRE function, you’ll help create it. You will define the frameworks, automation, and operational standards that ensure our model development infrastructure, distributed systems, and large compute clusters operate predictably, efficiently, and at scale.
This role sits at the intersection of AI research, large-scale cloud infrastructure, and production operations. Your work will directly enable faster model training, reliable experimentation, and scalable AI deployment by ensuring our cloud infrastructure is resilient and performant.
Key responsibilities
Reliability & Platform Ownership
Own the reliability, availability, and performance of the Model Dev Platform and GPU Compute environments.
Define and operationalise SLOs, SLIs, and error budgets across platform services.
Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.
Partner with ML, platform, and software teams to establish clear production readiness standards.
Incident Response & On-Call
Participate in a 24/7 on-call rotation as first-line response for cloud and cluster-related incidents.
Lead incident triage, escalation, communications, and root cause analysis.
Translate post-incident learning into durable architectural or automation improvements.
Continuously reduce alert noise and recurring operational burden.
Observability & Operational Excellence
Design and operate monitoring, logging, tracing, and alerting systems that enable rapid detection and recovery.
Build dashboards that reflect real user-centric platform health (not just infrastructure metrics).
Improve deployment safety through better change management, validation, and rollback mechanisms.
Automation & Tooling
Build automation for cluster operations, training workflows, remediation, and scaling tasks.
Implement self-healing patterns and resilient recovery workflows.
Harden CI/CD and release processes to improve deployment safety and velocity.
Support infrastructure-as-code and policy-driven guardrails to ensure secure, reliable cloud environments.
About you
In order to set you up for success as a Cloud Site Reliability Engineer at Wayve, we’re looking for the following skills and experience.
Essential skills
Proven experience in an SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems.
Strong Kubernetes experience, including operating production clusters.
Hands-on experience running production workloads in AWS, GCP, or Azure.
Experience operating complex distributed systems in production, ideally including compute-heavy or high-performance workloads.
Experience working with large compute clusters; exposure to AI/ML training or inference workloads strongly preferred.
Strong Linux fundamentals and proficiency in at least one scripting or systems language (e.g. Python, Go, C++) with a bias toward automation.
Deep troubleshooting skills across networking, storage, distributed systems, and performance at scale.
Experience designing and operating observability stacks (e.g. Datadog, Prometheus, Grafana, OpenTelemetry).
Clear communication skills, including leading incidents, writing postmortems, and influencing teams to prioritise reliability improvements.
Desirable skills
Experience operating GPU-backed environments or large-scale ML infrastructure.
Experience running model training or inference pipelines in production (MLOps).
Familiarity with infrastructure-as-code (e.g. Terraform) and secure cloud production environments.
Experience defining and running SLOs/SLIs and building reliability programs across multiple teams.
Experience as an early or founding SRE hire establishing processes from scratch.
Interest in helping shape and grow a Cloud SRE function, with potential to take on leadership responsibilities over time.
This is a full-time role based in our office in London (2 days a week in the office). At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.
A quick, honest note before you apply.
Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.
If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.
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