At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as 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 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.

At Wayve, 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!

The role 

We are looking for a Software Engineer to help build the Wayve Machine Learning platform. The ML Platform team owns the machine learning training infrastructure and works with users to ensure that this infrastructure is reliable and efficiently utilised.

Key responsibilities:

You will be part of a growing group focussed on making training infrastructure available to users, for distributed training of large models. You will be working across functions with machine learning research engineers to optimise models so that they can be trained efficiently, saving both money and researcher time. You will have opportunities to develop new skills, especially in model optimisation.

Examples Projects:

Working with machine learning researchers to optimise ML models, using the latest tooling like NVIDIA NSight. Training job scheduling and orchestration e.g. tooling to schedule long running jobs at off-peak times. Tooling which provides thousands of GPUs simultaneously to our driving simulator, which we use to test the driving performance of our models off road.

About you

In order to set you up for success in this role at Wayve, we’re looking for the following skills and experience.

Essential

Minimum of 5 years experience within Software Engineering, ideally ML Infrastructure / Platform Engineering Proficiency in Python Knowledge of software engineering practices - what makes code reusable and extensible. Experience working with concurrent, parallel and distributed computing. Passion for infrastructure: building internal tooling and frameworks. Experience with cloud infrastructure, preferably Azure Experience with Docker, Kubernetes and Terraform 

Desirable

Experience profiling and optimising ML models e.g. with NVIDIA NSight. Experience working with at least one ML framework e.g. Pytorch, Tensorflow, ONNX and TensorRT

#LI-HH1

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

For more information visit Careers at Wayve. 

To learn more about what drives us, visit Values 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 look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.