Machine Learning Engineer, Driving Product

Whereby; Greater London; Hybrid; GBP 110,000 - 170,000; Full time

Job summary

Wayve is hiring Senior and Staff ML Engineers that sit within the Driving Product organisation, building critical behaviours for L2 to L4 driving. You will train and iterate on end-to-end driving models and get them shipped into the car on a fast timeline measured in months.

You will own the full loop from data and training through evaluation and on-road validation, with direct impact on high-priority commercial deliveries (including the Nissan production and Robotaxi).

Qualifications

• Proven experience training deep learning models with end-to-end ownership (data, training, evaluation, iteration).
• Experience taking ML models into production with real-world constraints, quality and safety requirements.

Responsibilities

• Develop the AI driver model architecture and training algorithms for L2/L3/L4 driving behaviors.
• Own key parts of the training model lifecycle, including evaluation strategy and metrics.
• Mine, bucket, and curate real-world and synthetic data to teach driving behaviors.
• Run on-road and offline experiments, translate results into next steps and improvements.

Skills

Deep learning

End-to-end ML

Reinforcement learning

Transformer networks

Automotive domain

Data handling

Tools

PyTorch Lightning

Job description

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.

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 hiring Senior and Staff ML Engineers that sit within Driving Product organisation, building critical behaviours for Level 2 to level 4 driving. It is highly product-focused: you will train and iterate on end-to-end driving models and get them shipped into the car on a fast timeline measured in months. The opportunity is to own the full loop from data and training through evaluation and on-road validation, with direct impact on high-priority commercial deliveries (including the Nissan production and Robotaxi). You will join a small, high-ownership teams at the point of rapid growth, where execution and real-world outcomes matter.

Key responsibilities

• Develop the AI driver model architecture and training algorithms to introduce and enhance the driving behaviors for L2/L3/L4
• Own key parts of the training model lifecycle, including evaluation strategy, success metrics, and iteration planning.
• Mine, bucket, and curate real-world and synthetic data to teach specific driving behaviors, and implement data schemes to support training.
• Run and analyse on-road and offline experiments, translate results into clear next steps, and drive improvements through repeated training cycles.

About you

In order to set you up for success as a Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.

Essential

• Proven experience training deep learning models, with clear end-to-end ownership (data, training, evaluation, iteration).
• Experience taking ML models into production, including working through real-world constraints and quality and safety requirements

Desirable

• Reinforcement learning experience (especially where it materially improved real-world performance).
• Experience with end-to-end driving models and / or transformer networks
• Automotive or OEM experience, or prior work that involved deploying ML into physical systems.
• Experience with a Pytorch lightning training infrastructure
• Experience with model compression and deployments to embedded systems

This is a full-time role based in our office in Sunnyvale, London or Israel. 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

Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.

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.

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.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

For US candidates only, please visit E-Verify Notice and Participation and Right to Work

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.