Senior Cloud SRE - AI/ML Platform & GPU Compute
Senior Cloud SRE - AI/ML Platform & GPU Compute

Senior Cloud SRE - AI/ML Platform & GPU Compute

Full-Time 60000 - 80000 ÂŁ / year (est.) Home office (partial)
Wayve

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 60000 - 80000 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.

Senior Cloud SRE - AI/ML Platform & GPU Compute employer: Wayve

Wayve is an exceptional employer that fosters a dynamic and innovative work culture, particularly for those passionate about AI and cloud technologies. With a hybrid working policy that balances collaboration in our London office with the flexibility of remote work, employees benefit from a supportive environment that encourages personal growth and professional development. As a founding Cloud SRE, you will have the unique opportunity to shape the reliability foundations of our cutting-edge AI platform, making a meaningful impact while enjoying a commitment to inclusivity and diversity.
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

✨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, it shows you're genuinely interested in joining our team at Wayve. Don’t miss out on this opportunity!

We think you need these skills to ace Senior Cloud SRE - AI/ML Platform & GPU Compute

Site Reliability Engineering (SRE)
Kubernetes
AWS
GCP
Azure
Distributed Systems
AI/ML Workloads
Linux Fundamentals
Scripting Languages (Python, Go, C++)
Troubleshooting Skills
Observability Stacks (Datadog, Prometheus, Grafana, OpenTelemetry)
Incident Management
Infrastructure-as-Code (Terraform)
SLOs/SLIs Definition
MLOps

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with cloud systems and SRE roles. We want to see how your skills align with the responsibilities outlined in the job description.

Showcase Your Technical Skills: Don’t hold back on showcasing your technical expertise, especially in Kubernetes, AWS, GCP, or Azure. We’re looking for hands-on experience, so include specific projects or achievements that demonstrate your capabilities.

Communicate Clearly: Your written communication skills are key! When writing your application, be clear and concise. We want to see how you articulate complex ideas, especially when it comes to incident response and reliability improvements.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process!

How to prepare for a job interview at Wayve

✨Know Your Cloud Inside Out

Make sure you brush up on your knowledge of cloud platforms like AWS, GCP, or Azure. Be ready to discuss your hands-on experience with production workloads and how you've tackled challenges in large-scale cloud systems.

✨Show Off Your SRE Skills

Prepare to talk about your experience in Site Reliability Engineering. Highlight specific examples where you've defined SLOs, SLIs, or improved incident response processes. This is your chance to demonstrate how you can contribute to building a reliable AI cloud platform.

✨Get Familiar with Kubernetes

Since strong Kubernetes experience is essential, make sure you can discuss your experience operating production clusters. Be prepared to explain how you've managed complex distributed systems and any automation you've implemented to streamline operations.

✨Communicate Clearly and Confidently

Effective communication is key, especially when leading incidents or writing postmortems. Practice articulating your thoughts clearly and confidently, as this will help you influence teams and prioritise reliability improvements during the interview.

Senior Cloud SRE - AI/ML Platform & GPU Compute
Wayve

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