Principal Engineer, Data & Compute

Job description

Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams At Wayve, we teach machines to drive by training end-to-end neural networks that learn from large volumes of real-world data, not by coding rules. That takes a lot of data infrastructure and compute orchestration: our workloads span thousands of GPUs, petabytes of driving data, and training and inference clusters in several regions. Our AI Infrastructure team builds the compute and storage systems behind our model development lifecycle. 🧠 Your day-to-day As Principal Engineer, you'll design and guide how our core compute and storage systems evolve. You'll work across AI, systems and cloud infrastructure, speeding up AI research, enabling fast model deployment and keeping the platform ahead of the company's demands. You'll advise leadership on compute investment and help engineers across the org grow through architectural coaching and technical deep dives. 🧩 What you'll be working on - Global compute strategy: defining and evolving how Wayve allocates and orchestrates training and inference workloads across thousands of GPUs and multiple data centres, for throughput, resiliency and cost efficiency - Petabyte-scale data federation: designing systems for fast, reliable access to high-volume sensor and simulation data across geographies, and preparing Wayve to operate at exabyte scale - Cross-region GPU job execution: building the foundations for large-scale AI workloads to run across hybrid and multi-cloud environments - Cloud infrastructure advisory: helping leadership align compute investment and architecture with company strategy, growth plans and performance goals - Technical leadership and mentorship: coaching engineers on architecture, leading technical deep dives, and building a culture of operational and engineering excellence 🙌 You should apply if - You have 10+ years designing and building large-scale distributed systems, with at least 4 years focused on GPU-based cloud infrastructure - You have enabled large-scale AI training, inference or computer vision workloads in GPU clusters - You understand petabyte-scale data architecture in depth, including storage federation, high-throughput access and data locality for AI workloads - You have a track record of defining and communicating architectural strategy, balancing long-term vision with delivery needs - You mentor naturally, with a history of developing engineers and influencing technical direction across teams - You have an advanced degree in Computer Science, Electrical Engineering or a related field, or equivalent industry experience Nice to have: - Experience with multi-cloud orchestration, particularly in latency- or cost-sensitive training and inference pipelines - Familiarity with systems like Ray, Kubernetes, Airflow or Flyte, and fluency in AI/ML job scheduling, model lifecycle management and infrastructure-as-code - Background supporting safety-critical or real-time inference use cases (e.g. robotics, autonomous vehicles, aerospace) - An interest in building infrastructure as a product that gives research and product teams performance and simplicity 🌱 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. More about Wayve: 🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines. Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM