Applied Scientist



Vancouver, BC, Canada
Posted on Friday, April 12, 2024

Who are we?

Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning, computer vision and reinforcement learning. Leveraging our multi-national world-class team of researchers and engineers, we’re using data to learn more intelligent algorithms to bring autonomy for everyone, everywhere. We aim to be the future of self-driving cars, learning from experience and data.

Impact expected

We are seeking an experienced researcher to be a founding member of our Vancouver team! We are prioritising someone with experience actively participating in AI projects applied to autonomous driving or similar robotics or decision-making domains, inclusive, but not limited to the following specific areas:

  • Foundation models for robotics or embodied AI
  • Model-free and model-based reinforcement learning
  • Offline reinforcement learning
  • Large language models
  • Planning with learned models, model predictive control and tree search
  • Imitation learning, inverse reinforcement learning and causal inference
  • Learned agent models: behavioural and physical models of cars, people, and other dynamic agents

Challenges you will own

You'll be working on some of the world's hardest problems, and able to attack them in new ways. You'll be a key member of our diverse, cross-disciplinary team, helping teach our robots how to drive safely and comfortably in complex real-world environments. This encompasses many aspects of research across perception, prediction, planning, and control, including:

  • How to leverage our large, rich, and diverse sources of real-world driving data
  • How to architect our models to best employ the latest advances in foundation models, transformers, world models, etc, evaluating and incorporating state-of-the-art techniques into our workflows.
  • Which learning algorithms to use (e.g. reinforcement learning, behavioural cloning)
  • How to leverage simulation for controlled experimental insight, training data augmentation, and re-simulation
  • How to scale models efficiently across data, model size, and compute, while maintaining efficient deployment on the car
  • Collaborate with cross-functional teams to integrate research findings into scalable, production-level solutions.
  • You also have the potential to contribute to academic publications for top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc. working in a world-class team, contributing to the scientific community and establishing Wayve as a leader in the field.

What you will bring

Must haves:

  • Proven track record of research in one or more of the topics above demonstrated through deployed applications or publications.
  • Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch, numpy, pandas, etc.
  • Experience bringing a machine learning research concept through the full ML development cycle
  • 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.


  • Experience bringing an ML research concept through to production and at scale
  • PhD in Computer Science, Computer Engineering, or a related field

What we offer you

  • A position to shape the future of autonomous driving and embodied AI, and thus to tackle one of the biggest challenges of our time
  • Immersion in a team of world-class researchers, engineers and entrepreneurs
  • Competitive compensation and share options
  • Daily lunches, team socials, funded club/society activities and company-wide learning and development
  • Help relocating to Vancouver, with potential for visa sponsorship

Wayve is built by people from all walks of life. We believe that it is our differences that make us stronger, and our unique perspectives and backgrounds that allow us to build something different. We are proud to be an equal opportunities workplace, where we don’t just embrace diversity but nurture it - so that we all thrive and grow.