Senior Cloud Sre - Ai/ml Platform & GPU Compute

Wayve Wayve · Robotics · London, United Kingdom · AI Platform

Founding Cloud SRE role to build and scale the reliability foundations of Wayve's AI cloud platform, including the Model Development Platform and GPU Compute platform, supporting model training and inference at scale.

What you'd actually do

  1. Own the reliability, availability, and performance of the Model Dev Platform and GPU Compute environments.
  2. Define and operationalise SLOs, SLIs, and error budgets across platform services.
  3. Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.
  4. Partner with ML, platform, and software teams to establish clear production readiness standards.
  5. Participate in a 24/7 on-call rotation as first-line response for cloud and cluster-related incidents.

Skills

Required

  • SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems
  • Kubernetes experience, including operating production clusters
  • running production workloads in AWS, GCP, or Azure
  • operating complex distributed systems in production, ideally including compute-heavy or high-performance workloads
  • working with large compute clusters
  • Linux fundamentals
  • Python, Go, C++
  • troubleshooting skills across networking, storage, distributed systems, and performance at scale
  • 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

Nice to have

  • 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

What the JD emphasized

  • founding Cloud SRE role
  • help create it
  • define the frameworks, automation, and operational standards
  • intersection of AI research, large-scale cloud infrastructure, and production operations
  • directly enable faster model training, reliable experimentation, and scalable AI deployment
  • 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.
  • 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.

Other signals

  • founding Cloud SRE role
  • build and scale the reliability foundations of our AI cloud platform
  • Model Development Platform
  • GPU Compute platform
  • large-scale, multi-tenant GPU fleets and scheduling systems driving model training and inference at scale