Staff ML Performance Engineer (Training Efficiency)
Wayve is seeking a Staff ML Performance Engineer to join their Training Tech team. This role focuses on optimizing large-scale ML jobs and increasing the efficiency of training and inference workloads, enabling faster training of larger models. The ideal candidate will profile ML workloads, design and implement efficiency improvements, and collaborate with Research teams to integrate performance optimizations.
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 are looking for a Staff ML Performance Engineer to join our Training Tech team working on optimizing large scale ML jobs to enable scaling our models to the next order of magnitude. A successful candidate will increase efficiency of training and inference workloads in order to allow Wayve to train larger models faster.
In order to set you up for success in this role, we’re looking for the following skills and experience.
Posted May 27, 2026