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About the Role

At Wayve, we are teaching machines to drive using end-to-end neural networks trained on real-world data. This requires massive scale in data infrastructure and compute orchestration, spanning thousands of GPUs and petabytes of data. As Architect for AI Infrastructure, you will design and guide the evolution of foundational compute and storage systems, directly accelerating AI research, enabling rapid model deployment, and ensuring our platform meets the demands of autonomy.

Responsibilities

Define and evolve the architecture for allocating and orchestrating training and inference workloads across thousands of GPUs and multiple data centers, ensuring optimal throughput, resiliency, and cost efficiency.
Design systems that enable fast, reliable access to high-volume sensor and simulation data across geographies, ensuring the right data is always available for training, evaluation, and inference, and preparing Wayve for being an exabyte-scale company.
Build the foundations that enable large-scale AI workloads to run seamlessly across hybrid and multi-cloud environments.
Act as a trusted partner to leadership in aligning compute investments and architecture with company strategy, growth plans, and performance goals.
Uplift the broader engineering org through architectural coaching, technical deep dives, and by cultivating a culture of operational and engineering excellence.

Requirements

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

Skills

Multi-cloud orchestration
Ray
Kubernetes
Airflow
Flyte
AI/ML job scheduling
Model lifecycle management
Infrastructure-as-code practices
Supporting safety-critical or real-time inference use cases
Robotics
Autonomous vehicles
Aerospace
Building infrastructure-as-a-product

Location

Sunnyvale, CA

Work Type

Full-time
Hybrid

Experience Level

10+ years designing and building large-scale distributed systems
4+ years focused on GPU-based cloud infrastructure

Education Level

Advanced degree in Computer Science, Electrical Engineering, or a related field
Equivalent industry experience

Salary/Compensations

$370,300 to $418,200

Benefits

Competitive equity package

About the Company

At Wayve, we are teaching machines to drive—not by coding rules, but by training end-to-end neural networks that learn from vast streams of real-world data.
Achieving this requires unprecedented scale in both data infrastructure and compute orchestration. Our workloads span thousands of GPUs, petabytes of driving data, and geographically distributed training and inference clusters.