Engineering Manager - Compute and Data Platform (AI Platform)

In this role you lead Wayve’s Compute Foundations team in London, building a reliable, high-performance multi-cloud platform for training and inference. You shape strategy, roadmap and cross-team collaboration to maximise system availability, performance and cost efficiency. You mentor engineers, scale the team, and partner with cloud providers to support the Wayve Driver at scale. You’ll operate at the intersection of GPU compute, storage and orchestration to enable world-class AI workloads.

• salary benchmarked against market
• equity share in Wayve
• relocation support and visa sponsorship
• hybrid working with core hours
• learning and development budgets
• comprehensive health and dental benefits

• Lead and develop the engineering team, providing coaching, performance management and career growth
• Oversee hiring and onboarding to scale the team and build technical leadership
• Own roadmap prioritisation, surface risks and align delivery with stakeholders
• Guide evolution of a multi-cloud, multi-region training & inference platform
• Improve scheduling, resource allocation and Kubernetes-based infrastructure across heterogeneous GPUs
• Plan capacity and cost with stakeholders and cloud providers
• Guide distributed storage and data locality to reduce duplication and cross-cloud data transfers

• Strong track record managing infrastructure/platform or distributed systems teams
• Experience delivering through others with emphasis on reliability and platform improvement
• Substantial Kubernetes and workload scheduling experience (e.g., Kueue)
• Ability to reason about availability, capacity, performance and cost in complex cloud setups
• Understanding of large-scale GPU compute infrastructure for ML training/inference
• Ability to earn engineers’ trust with sound technical judgment without being the sole IC
• Clear communication with technical teams, stakeholders and external providers
• Willingness to work from the London office and lead a local team

• leadership and coaching
• stakeholder management
• clear communication
• Kubernetes and workload queuing/scheduling systems (Kueue)
• multi-cloud/multi-region platform operations
• GPU architectures (Nvidia Hopper, Blackwell; Qualcomm)