Machine Learning Engineer, Reinforcement Learning & Reward Modeling

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Join to apply for the Applied Scientist - Reward Modeling role at Wayve

Join to apply for the Applied Scientist - Reward Modeling role at Wayve

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.

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!

The role

We're looking for an experienced Applied Scientist with expertise in Reinforcement Learning and Reward Modelling to advance our training and evaluation frameworks contributing significantly to the creation of safe and reliable AI driving technology. The ideal candidate has a deep understanding of reinforcement learning, machine learning, and behavioural modelling, combined with a drive to innovate in the autonomous driving space.

Role

In this role, you will be at the forefront of designing and optimizing reward and reinforcement learning models that are powerful and resource-efficient, tailored for the unique demands of embodied AI and autonomous systems. Your work will involve but not limited to :

• Design, develop, and refine reward models that align with safe and efficient driving objectives for autonomous vehicles.
• Work closely with multidisciplinary teams to integrate reward models with real-world data and simulation frameworks.
• Define a data strategy that includes efficient use of real and synthetic data, annotations, and active learning.
• Design experiments to evaluate reward structures in diverse driving scenarios and identify areas for improvement.
• Collaborate with world-class researchers and engineers to push the boundaries of AI, contributing significantly to the evolution of autonomous driving technology

What you’ll bring to Wayve

In order to set you up for success as an Applied Scientist at Wayve, we’re looking for the following skills and experience.

Must Haves

Desirable

What we offer you

This is a full-time role based in our office in Vancouver. 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 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.

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Research, Analyst, and Information Technology

Industries

Software Development

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