Principal Engineer, Compute

Wayve • Sunnyvale, CA

13d • $407,330 - $460,020 • Hybrid

About The Position

Wayve’s AI Infrastructure team builds the compute and storage systems supporting development of its end-to-end autonomous-driving models. These systems serve workloads spanning thousands of GPUs, petabytes of driving data, and training and inference clusters in several regions.

As Principal Engineer, Compute, you will design and guide the evolution of core compute and storage systems. You will work across AI, systems, and cloud infrastructure to accelerate AI research, enable fast model deployment, and keep the platform aligned with company needs. The role also advises leadership on compute investment and helps engineers across the organization grow through architectural coaching and technical deep dives.

Wayve builds an AI platform for autonomous driving that learns from real-world experience. The company operates a hybrid working model, combining in-person collaboration at dedicated offices with remote work. Its main hubs are London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg.

Requirements

• 10+ years designing and building large-scale distributed systems, including at least 4 years focused on GPU-based cloud infrastructure.
• Experience enabling large-scale AI training, inference, or computer vision workloads in GPU clusters.
• In-depth understanding of petabyte-scale data architecture, including storage federation, high-throughput access, and data locality for AI workloads.
• Track record defining and communicating architectural strategy while balancing long-term vision with delivery needs.
• Experience mentoring and developing engineers and influencing technical direction across teams.
• Advanced degree in Computer Science, Electrical Engineering, or a related field, or equivalent industry experience.

Nice To Haves

• Experience with multi-cloud orchestration, particularly for latency- or cost-sensitive training and inference pipelines.
• Familiarity with 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, such as robotics, autonomous vehicles, or aerospace.
• Interest in building infrastructure as a product that gives research and product teams performance and simplicity.

Responsibilities

• Define and evolve global compute strategy for allocating and orchestrating training and inference workloads across thousands of GPUs and multiple data centres, balancing throughput, resiliency, and cost efficiency.
• Design systems for fast, reliable access to high-volume sensor and simulation data across geographies and prepare the platform to operate at exabyte scale.
• Build foundations for large-scale AI workloads to run across hybrid and multi-cloud environments.
• Advise leadership on compute investment and architecture in relation to company strategy, growth plans, and performance goals.
• Coach engineers on architecture, lead technical deep dives, and foster operational and engineering excellence.
• Work across AI, systems, and cloud infrastructure to accelerate research and enable rapid model deployment.

Benefits

• Market-benchmarked salaries reviewed annually.
• Meaningful equity.
• Relocation support and visa sponsorship where applicable.
• Hybrid working and core hours.
• Opportunity 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, and team socials.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal