Applied Scientist - Multimodal Modeling London; Sunnyvale; Vancouver

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. 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.

The role We’re looking for a Senior Applied Scientist to join the core team building Wayve’s next-generation Foundation Model for autonomy. This is a rare opportunity to work on a high-impact, multi-modal model—combining video, LiDAR, radar, and language—designed for real-world deployment at scale. You’ll be embedded in a small, high-leverage team in London, contributing directly to modeling breakthroughs in scaling laws, mixture-of-experts, and attention architectures. Your work will help define how embodied AI systems learn to act in complex, dynamic environments.

• Design and scale core components of the Wayve Foundation Model (e.g. attention, MoE, KV caching)
• Lead empirical research on scaling laws for multi-modal models
• Develop and optimize distributed training strategies (e.g. FSDP, large-batch training)
• Collaborate with teams across perception, policy, and infra to integrate and evaluate model improvements
• Contribute to the broader research community through papers, benchmarks, and shared insights

• Experience developing and training large-scale machine learning models, ideally foundation models
• Strong understanding of modern modeling techniques such as Transformers, Mixture-of-Experts, and attention variants (e.g. linearized or memory-efficient attention)
• Applied experience with multi-modal data (e.g. video, LiDAR, radar, and/or language)
• Solid background in distributed training and scaling infrastructure (e.g. FSDP, KV caching, large-batch optimization)
• 3–5 years of experience post-PhD or equivalent industry experience in applied ML research
• Familiarity with training frameworks such as PyTorch, JAX, DeepSpeed, or custom infra for large models
• Demonstrated track record of publications in top-tier ML/CV conferences (e.g. NeurIPS, ICLR, ICML, CVPR)
• Hands-on contributions to scaling law research or empirical model scaling at scale
• Experience working on models for real-world robotics, autonomy, or perception
• Experience in autonomous driving or end-to-end learning.

• 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 leave.