Join to apply for the Machine Learning Engineer - Pre-Training role at Wayve.

At Wayve, we are committed to creating a diverse, fair, and respectful culture that is inclusive of everyone regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law.

About Us

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 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.

The Role

We are seeking skilled engineers to join our Training Tech team, working on optimizing large-scale training jobs to scale our models through the next order of magnitude. The successful candidate will increase the efficiency of training jobs to allow Wayve to train larger models faster.

Key Responsibilities

• Profile training jobs to identify bottlenecks, e.g. using NVIDIA Nsight Systems.
• Design and implement efficiency improvements to maximize MFU, e.g. tensor parallelism, model compilation, mixed precision.
• Design and implement observability tools, e.g. to track MFU.
• Collaborate closely with Research teams to integrate training efficiency improvements and create a culture of performance optimization.

About You

Essential qualifications and experience:

• Experience optimizing large-scale training jobs on GPU compute clusters.
• Experience working in platform teams and with research teams.
• Experience reporting and tracking benchmarked performance over time in an open and accessible way.
• Ability to write high-quality, well-structured, and tested Python code.
• BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline, or equivalent experience.

Desirable skills

• Solid experience working with concurrent, parallel, and distributed computing.
• Experience using NVIDIA Nsight Systems.
• Experience implementing GPU kernels.
• Knowledge of computing fundamentals—what makes code fast, secure, and reliable.

Location & Working Policy

This is a full-time role based in our London office. We operate a hybrid working policy that combines time together in our offices and workshops with time working from home. You can shape your schedule around core working hours while collaborating with a high-performing team.

We understand that not every applicant will meet all of the requirements listed above. If you’re passionate about self-driving cars and believe you can positively impact the world, we encourage you to apply.

For more information, visit Careers at Wayve.

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do capture information about care responsibilities, disabilities, and other diversity data through an optional DEI monitoring form to help improve our hiring process and ensure it is inclusive and non-discriminatory.