Applied Scientist, Wayve Foundation Models

As an Applied Scientist at Wayve, you'll be responsible for the design and development of end-to-end neural networks that enhance autonomous driving capabilities. You'll collaborate with Production and Research Engineers to develop, test, scale, and deploy advanced ML models, ensuring they meet our standards of efficiency and performance.

Candidates for the Applied Scientist position at Wayve should have a proven track record in large-scale multimodal modelling or related fields. Essential skills include strong programming capabilities in Python, familiarity with deep learning frameworks like PyTorch, and experience in the full ML development cycle. A Master's or Ph.D. in Computer Science or Engineering with a focus on Machine Learning or AI is beneficial.

Wayve promotes a dynamic and fast-paced work environment that values creativity and innovation. We operate on a hybrid working policy, allowing our Applied Scientists to enjoy flexibility while collaborating in-person at our Vancouver office. Together, we nurture learning and growth, fostering a culture that is respectful, ego-free, and inclusive.

At Wayve, we prioritize the personal and professional development of our Applied Scientists. You'll learn on the job from some of the brightest minds in the AI and automotive industries, and we encourage formal learning opportunities to help you enhance your skills. Your growth is important to us as we work towards shaping the future of autonomous vehicles!

An Applied Scientist at Wayve holds the potential to significantly influence the development of our autonomous driving technology. Through your expertise in developing advanced ML models, your contributions will help us create intelligent systems that improve vehicle perception and navigation, ultimately advancing safety and usability in automated driving.

When discussing your experience with large-scale deep learning models, highlight any projects where you developed or improved models specifically for autonomous systems. Mention techniques you utilized, challenges you faced, and the methodologies involved in training and deploying these models effectively.

In your answer, emphasize your hands-on experience with frameworks like PyTorch or TensorFlow. You might discuss specific projects where you utilized these tools to build, train, or optimize models, along with any libraries like Numpy or Pandas that enhanced your workflows.

Describe your systematic approach to model evaluation, detailing your familiarity with metrics such as accuracy, precision, recall, and F1 score. Share examples of how these evaluations guided your iterations or optimizations, helping you achieve better model performance.

Discuss specific techniques for integrating and processing multimodal data, such as feature engineering or preprocessing strategies. Include examples from your past projects that demonstrate your ability to manage and derive insights from diverse datasets, showing your understanding of the complexities involved.

Share a specific instance where you encountered challenges during the deployment of a machine learning model. Explain the problem, your thought process in analyzing it, and the steps you took to resolve the issue, emphasizing your problem-solving skills and adaptability.

Highlight your ability to work collaboratively across disciplines. Provide an example of a project involving engineers, data scientists, or product managers, and explain how effective communication and teamwork played a critical role in your success.

Express your passion for innovation in autonomous driving and machine learning, discussing personal experiences or interests that align with Wayve’s mission. Highlight your excitement about contributing to groundbreaking advancements in the field.

Share your strategies for keeping up with industry trends, such as following reputable journals, participating in online communities, attending conferences, or engaging in continued education. Highlight any recent findings that have impacted your work positively.

Discuss various ethical challenges associated with AI in autonomous vehicles, such as bias, safety, and privacy concerns. Express your commitment to responsible AI practices and how attention to ethics can enhance public trust in self-driving technologies.

Discuss both your career aspirations and how you envision contributing to Wayve’s mission. You could talk about your desire for meaningful work and learning opportunities, as well as your hope to make a significant impact within the team and broader field.