EngineersOfAI · London, United Kingdom ·
Software engineer on Wayve's AI Libraries team, building scalable Python libraries and training infrastructure (data loading, distributed training, checkpointing, evaluation) that let ML researchers train and scale autonomous-driving models across GPU clusters and Azure cloud.
Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.
Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.
At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.
Make Wayve the experience that defines your career!
We’re looking for a Software Engineer to join our AI Libraries team. This team builds and maintains the platforms, libraries, and tools that enable Wayve’s ML engineers and researchers to train, evaluate, and scale models efficiently.
This is a hands-on software engineering role focused on building stable, scalable, and modular systems that support large-scale ML development. You’ll work closely with ML teams across Wayve to understand their needs, design reusable abstractions, and improve the reliability, performance, and usability of our training infrastructure.
You’ll play a key role in maturing Wayve’s AI platform and helping bring autonomous driving technology into the hands of customers.
We’re looking for a strong software engineer who enjoys building high-quality tools, platforms, and libraries for technical users. You care about clean abstractions, scalable architecture, reliability, and creating software that other engineers can depend on.