At a Glance
- Tasks: Build and scale the reliability foundations of our AI cloud platform.
- Company: Join Wayve, a pioneering tech company in self-driving cars.
- Benefits: Enjoy a hybrid work model, competitive salary, and professional growth opportunities.
- Other info: Be part of a dynamic team with potential leadership opportunities.
- Why this job: Shape the future of AI with cutting-edge technology and make a real impact.
- Qualifications: Experience in SRE roles, Kubernetes, and cloud systems is essential.
The predicted salary is between 70000 - 90000 ÂŁ per year.
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.
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.
Senior Cloud SRE - AI/ML Platform & GPU Compute in London employer: Wayve
Contact Detail:
Wayve Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Cloud SRE - AI/ML Platform & GPU Compute in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to cloud infrastructure or AI/ML. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common SRE scenarios. Think about how you'd handle incidents or improve system reliability. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Senior Cloud SRE - AI/ML Platform & GPU Compute in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Cloud SRE role. Highlight your experience with large-scale cloud systems, Kubernetes, and any relevant AI/ML projects. We want to see how your skills align with what we're looking for!
Showcase Your Problem-Solving Skills: In your application, share examples of how you've tackled complex issues in production environments. We love seeing candidates who can demonstrate their troubleshooting skills and how they've improved reliability in past roles.
Be Clear and Concise: When writing your cover letter, keep it straightforward and to the point. We appreciate clarity, so make sure you communicate your passion for the role and how you can contribute to our team without fluff.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Wayve
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Kubernetes and cloud platforms like AWS, GCP, or Azure. Brush up on your Linux fundamentals and scripting skills, as these will be crucial for the role.
✨Demonstrate Problem-Solving Skills
Prepare to discuss specific incidents where you’ve successfully troubleshot complex distributed systems. Be ready to explain your thought process during these situations, as this will showcase your deep troubleshooting skills and ability to handle pressure.
✨Showcase Your Automation Experience
Highlight any past experiences where you’ve built automation for cluster operations or implemented self-healing patterns. Discuss how these improvements have led to increased efficiency and reliability in previous roles.
✨Communicate Clearly and Confidently
Practice articulating your thoughts clearly, especially when discussing technical concepts. Being able to lead incidents and write postmortems effectively is key, so consider preparing a few examples of how you’ve communicated with teams in high-pressure situations.