wayve - Engineering Manager - Compute and Data Platform (AI Platform)
Responsibilities
• People leadership will be your first priority. You’ll coach and develop engineers, set clear expectations, manage performance. You’ll build technical leadership within the team, giving engineers the support and ownership they need to grow. You will guide the growth of the team through hiring and onboarding. • Alongside this, you will own project prioritisation and roadmap planning, aligning priorities and delivery plans with stakeholders across Wayve. Your goal is to maximise the impact of the team in alignment with the department and company objectives. You will provide visibility into the state of systems you own through clear KPIs and dashboards. • Leading a highly technical team, you’ll bring the technical judgement to guide complex infrastructure decisions and turn competing needs into a clear roadmap. Working with technical leads, partner teams and cloud providers, you’ll balance reliability, performance, capacity and cost, and help the team deliver sustainably. • 🧩 What you’ll be working on • Leading and developing the team: Coach engineers through regular feedback and one-to-ones, manage performance, support career development and build a healthy, performant and accountable team. • Hiring and building technical leadership: Lead hiring and onboarding as the team expands, and develop technical leads who can take ownership of key areas of the platform. • Driving the roadmap and delivery: Translate training and inference needs into priorities, align commitments with available resources, and surface risks and dependencies early. • Scaling cloud compute: Guide the evolution and operation of a multi-cloud, multi-region training and inference platform, including the adoption of new compute architectures (Nvidia Hopper, Blackwell; Qualcomm). • Improving scheduling and availability: Oversee Kubernetes-based infrastructure and queuing and scheduling systems, enabling workloads to use the right resources across heterogeneous GPU environments. • Planning capacity and cost: Partner with stakeholders and cloud providers on compute and storage forecasts, accounting for resource lead times, performance requirements and cost trade-offs. • Ensuring efficient storage across clouds: Guide distributed storage and caching approaches that improve data access and reduce unnecessary duplication and cross-cloud transfer costs. • 🙌 You should apply if • 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 communicate clearly with technical teams, stakeholders and external providers, and can turn ambiguous requirements into practical priorities. • You are able to work from our London office and lead a team based there. • The following experience would be useful but is not required: • Operating multi-cloud or multi-region platforms for large-scale AI workloads. • Introducing new GPU architectures or managing heterogeneous GPU fleets. • Distributed storage, caching and data-locality strategies for data-intensive workloads. • Capacity forecasting, cloud cost modelling and close collaboration with cloud infrastructure providers. • 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.
Benefits
• 💰 Salaries benchmarked against the market annually • 📈 Meaningful equity, sharing in the ownership and long term success of Wayve • ✈️ Relocation support and visa sponsorship where applicable • ✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs • 📚 Learning and development budgets with support for training, conferences and growth • 🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more • Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one. • If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. • At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. • For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/
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