Staff SRE, AI Infrastructure in London

Staff SRE, AI Infrastructure in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Shape the reliability of AI systems and GPU infrastructure from the ground up.
  • Company: Wayve, a leader in Embodied AI technology with a focus on innovation.
  • Benefits: Hybrid working model, inclusive culture, and opportunities for career growth.
  • Other info: Join a diverse team committed to making a positive impact on the world.
  • Why this job: Be part of a pioneering team transforming automated driving with cutting-edge AI.
  • Qualifications: Experience in SRE roles, cloud systems, and strong Kubernetes skills.

The predicted salary is between 63000 - 77000 £ per year.

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

This is a rare opportunity to be a founding Staff SRE shaping the reliability of large-scale AI systems and GPU compute infrastructure from the ground up. As a Staff 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.
  • Experience operating GPU-backed environments or large-scale ML infrastructure.
  • Experience running model training or inference pipelines in production (MLOps).
  • 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:

  • 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.

Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

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.

Staff SRE, AI Infrastructure in London employer: wayve

Wayve is an exceptional employer, offering a dynamic and inclusive work culture that fosters innovation and collaboration. With a focus on employee growth, you will have the opportunity to work alongside talented AI engineers in a hybrid environment, contributing to groundbreaking advancements in autonomous driving while enjoying the vibrant atmosphere of London. Join us to make a meaningful impact in the field of AI and data science.

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Contact Details:

wayve Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff SRE, AI Infrastructure in London

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at wayve or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

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Tap into Online Developer Communities

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Explore Job Boards Specifically for Tech Roles

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We think you need these skills to ace Staff SRE, AI Infrastructure in London

Site Reliability Engineering (SRE)
Production Engineering
Cloud Reliability
GPU-backed environments
MLOps
Kubernetes
AWS

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at wayve.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at wayve and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at wayve

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If wayve uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.