Senior Applied Scientist
Synthetic Data
Confirmed live in the last 24 hours

201-500 employees

Develops embodied AI for scalable autonomous vehicles
Company Overview
Wayve stands out as a leader in the autonomous vehicle industry, pioneering the use of embodied AI to develop AV2.0, a next-generation approach to self-driving technology that is adaptable, lean, and affordable. The company's unique approach leverages end-to-end deep learning, eliminating the need for costly robotic stacks and complex mapping, and has already been deployed on public roads, demonstrating its practical viability. With a diverse team of experts and partnerships with leading retailers for real-world testing, Wayve offers a dynamic and impactful work environment focused on addressing significant global challenges.
AI & Machine Learning
Robotics & Automation

Company Stage

Series B

Total Funding





London, United Kingdom

Growth & Insights

6 month growth


1 year growth


2 year growth

London, UK
Experience Level
Desired Skills
Computer Vision
AI & Machine Learning
Applied Machine Learning
Deep Learning
AI Research
  • Proven expertise in synthetic data generation and application in AI model training and testing.
  • Strong foundation in machine learning, deep learning, and neural rendering techniques.
  • Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch.
  • Demonstrable experience with tools relevant to synthetic data generation.
  • 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 with dynamic scene reconstruction and rendering, particularly in outdoor environments.
  • Familiarity with parallel computing, GPU programming, and optimization techniques.
  • PhD or MSc in Computer Science, Computer Engineering, or a related field, with a focus on computer graphics, computer vision, or machine learning.
  • Lead the development and implementation of synthetic data generation techniques to support the training and testing of AI models.
  • Collaborate with cross-functional teams to understand requirements and create realistic, scalable synthetic datasets tailored to specific AI applications.
  • Apply state-of-the-art machine learning and deep learning methodologies to improve the fidelity and efficiency of synthetic data.
  • Conduct rigorous validation and testing of AI models using synthetic data, identifying and addressing gaps in performance.
  • Stay abreast of the latest research and technological advancements in synthetic data and neural rendering, integrating new findings into our workflows.