As a Staff Site Reliability Engineer, you will lead the architectural direction of our Kubernetes platform, tackle complex reliability challenges, and mentor engineers across teams.
Staff SRE, AI Infrastructure
📜 Description
- Identify reliability risks and turn recurring operational issues into durable engineering solutions.
- Improve observability, automation, deployment safety, capacity planning, and incident learning.
- Help teams adopt effective SLOs and production-readiness practices.
- Improve GPU node health detection and automated recovery, and strengthen distributed AI training resilience.
- Develop GitOps delivery and enhance Kubernetes scheduling, autoscaling, policy enforcement, and resource efficiency.
- Build GPU and storage capacity forecasting and reusable self-service platform capabilities.
🛠️ Requirements
- Hands-on experience owning reliability for large-scale cloud, Kubernetes, or distributed infrastructure.
- Recent practical experience coding, automating, configuring, or troubleshooting production systems.
- Comfort with Python or Go, infrastructure as code, CI/CD or GitOps, and modern observability practices.
- Understanding of distributed-systems failure modes across compute, networking, and storage.
- Evidence of measurable improvements to reliability, performance, capacity, or cost, and effective cross-team collaboration.
- GPU, ML-training, or HPC infrastructure experience is valuable; comparable large-scale platform experience is also relevant.
✨ Benefits
- Market-benchmarked salaries, reviewed annually
- Meaningful equity
- Relocation support and visa sponsorship where applicable
- Hybrid working and core hours
- Learning and development budgets, including training and conferences
- Health insurance
- Dental insurance
- Enhanced parental leave
- Retirement or pension where applicable
- Wellbeing partnerships
Full job description
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.
Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.
How we work 💻- Locations & Flexible Working:
Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.
🔍 The Interview Process:
Our process is clear and respectful of your time:
Initial call / recruiter screen
Competency Interviews
Deep-dive technical interviews
Final interview: mission & values alignment
We’ll always explain the format and work around your availability.
What’s in it for you (Location dependant):
💰 Salaries benchmarked against the market annually
📈 Meaningful equity, sharing in the ownership and long term success of Wayve
✈️ Relocation support and visa sponsorship where applicable
✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
📚 Learning and development budgets with support 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, team socials and more
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.
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.
For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve
DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
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