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Applied Scientist - Reward Modeling Vancouver
Applied Scientist - Reward Modeling VancouverWayve Technologies Ltd. • Vancouver, BC, CA
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Applied Scientist - Reward Modeling Vancouver

Applied Scientist - Reward Modeling Vancouver

Wayve Technologies Ltd. • Vancouver, BC, CA
30+ days ago
Job type
  • Full-time
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.

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.

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 :

  • Proven expertise in reinforcement learning, including in areas like offline RL, reward modelling, RLHF, DPO, GPRO, as well as experience with machine learning.
  • Strong programming skills in Python and experience with machine learning libraries such as PyTorch.
  • Experience in working with simulation environments and real-world data for model validation and performance benchmarking.
  • Demonstrated ability to publish research and present findings to both technical and non-technical audiences at top tier conferences.
  • Excellent problem-solving skills and the ability to work independently as well as in a team environment.
  • Demonstrated ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment.
  • Track record of publications at top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc.
  • Familiarity with self-driving technologies, sensor data processing, and real-time decision-making algorithms.
  • Experience with large-scale machine learning systems, distributed training and deploying models in production environments.
  • What we offer you

  • Attractive compensation with salary and equity
  • Immersion in a team of world-class researchers, engineers and entrepreneurs
  • A unique position to shape the future of autonomy and tackle the biggest challenge of our time
  • Bespoke learning and development opportunities
  • Relocation support with visa sponsorship
  • Flexible working hours - we trust you to do your job well, at times that suit you and your time
  • Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more!
  • 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.

    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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    Applied Scientist Reward Modeling Vancouver • Vancouver, BC, CA

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