Job Description

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're looking for leaders who can foster innovation, drive strategic initiatives, and steer teams towards achieving breakthroughs in data centric AI.

This role will sit in our Embodied AI division which consists of modelling, robotics, data and detectives teams working together to deliver an Autonomous Driving product.

We are looking for an experienced Machine Learning Engineer to help us in our journey to scale end-to-end neural networks for autonomous driving. You’ll be working across our embodied AI org team to build, integrate, test and scale algorithms, tools, and machine learning solutions for autonomous driving.

Challenges you will own

• Technical leadership of at least one company wide program
• Developing and implementing machine learning models and robotics systems to enhance the capabilities of our Autonomous Vehicle stack.
• Collaborating with cross-functional teams to contribute to the broader company strategy and roadmap, focusing on machine learning applications.
• Enhancing skills and knowledge in machine learning through continuous learning and application, while contributing to the growth and mentorship of junior engineers.
• Allocating personal bandwidth and technical resources effectively to meet both project requirements and personal professional development needs.
• Working with leadership and other teams to foster a culture that promotes collaboration, high impact, innovation, and a healthy work environment.
• Evaluating project decisions and outcomes, identifying dependencies, and analysing risks associated with machine learning deployments.
• Troubleshooting and optimising machine learning models and systems - identify potential issues, challenge existing assumptions, introduce innovative solutions, and implement feedback loops to enhance model performance.

About you

Essential

• 7+ years of software and machine learning engineering experience in an industrial or applied research environment
• Good insight into the practical aspects of training, validation, testing and metrics for deep learning features/models
• Passion to work in a team on research ideas that have real product impact
• A good grasp of machine learning literature, ideally published
• Comfortable working with large quantities of image and video data
• BSc above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience

Desirable

• Strong software engineering experience in Python and other relevant languages (e.g. C++ and CUDA)
• Direct experience working in at least one of computer vision, robotics, simulation, graphics, or large language models.
• MS, or above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience

What we offer you

• The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact
• Competitive compensation and benefits
• A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too
• A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day
• Benefits such as an onsite chef, workplace nursery scheme, private health insurance, cycle scheme, therapy, yoga, two onsite bars, large social budgets
• At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We also operate core working hours so you can be where you need to be for family and loved ones too. Teams determine the routines that work best for them

#LI-AF1

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.

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