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Wayve

End-to-end autonomous-driving software for vehicles

Engineering Manager - Compute and Data Platform

Engineering LeadershipUpdated on Nov 11
Full-timeLondon, UK

About the Job

Requirements

  • You have a strong track record of managing and developing an infrastructure, platform or distributed systems engineering team, including hiring, coaching, performance management and career development.
  • You have delivered through others, owning team priorities and balancing delivery with operational reliability and longer-term platform improvements.
  • You have substantial experience in Kubernetes and workload queuing and scheduling systems, such as Kueue or equivalent technologies.
  • You can reason about availability, capacity, performance and cost across complex cloud infrastructure, including the interaction between compute, storage and data movement.
  • You understand large-scale GPU compute infrastructure for machine learning training or inference and the operational challenges of scaling beyond small GPU deployments.
  • You can earn engineers’ trust through sound technical judgement without needing to be the team’s primary individual contributor. You have successfully delivered as an individual contributor in the past.
  • You can communicate clearly with technical teams, stakeholders and external providers, and turn ambiguous requirements into practical priorities.
  • You are able to work from the London office and lead a team based there.

Responsibilities

  • Lead and develop the team by coaching engineers through regular feedback and one-to-ones, managing performance, supporting career development, and building a healthy, performant and accountable team.
  • Lead hiring and onboarding as the team expands, and develop technical leads who can take ownership of key areas of the platform.
  • Translate training and inference needs into priorities, align commitments with available resources, and surface risks and dependencies early.
  • Guide the evolution and operation of a multi-cloud, multi-region training and inference platform, including adoption of new compute architectures such as Nvidia Hopper, Blackwell and Qualcomm.
  • Oversee Kubernetes-based infrastructure and queuing and scheduling systems, enabling workloads to use appropriate resources across heterogeneous GPU environments.
  • Partner with stakeholders and cloud providers on compute and storage forecasts, accounting for resource lead times, performance requirements and cost trade-offs.
  • Guide distributed storage and caching approaches that improve data access and reduce unnecessary duplication and cross-cloud transfer costs.
  • Own project prioritisation and roadmap planning, aligning priorities and delivery plans with stakeholders across the company.
  • Provide visibility into the state of owned systems through clear key performance indicators and dashboards.
  • Guide complex infrastructure decisions and balance reliability, performance, capacity and cost while supporting sustainable delivery.

Desired Qualifications

  • Experience operating multi-cloud or multi-region platforms for large-scale AI workloads.
  • Experience introducing new GPU architectures or managing heterogeneous GPU fleets.
  • Experience with distributed storage, caching and data-locality strategies for data-intensive workloads.
  • Experience with capacity forecasting, cloud cost modelling and close collaboration with cloud infrastructure providers.

About the Company

Wayve

End-to-end autonomous-driving software for vehicles

Wayve provides end-to-end autonomous-driving software for automakers and fleets that runs entirely on onboard compute and sensors, without relying on HD maps or city-by-city engineering. The system uses foundation models capable of zero-shot driving and has demonstrated ability to drive across 500+ cities in Europe, North America, and Japan. Unlike traditional AV stacks that depend on mapped data and per-city customization, Wayve aims to generalize driving with its onboard AI across diverse environments. Its goal is to scale commercial robotaxi trials from 2026 and bring supervised autonomy to consumer vehicles from 2027, backed by substantial funding partnerships to support rapid deployment.

Company size
1,001-5,000
Company stage
Series D
Total funding
$2.6B
Headquarters
London, United Kingdom
Founded
2017

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