Wayve is looking for a Senior Applied Scientist to build the company's next-generation Foundation Model for autonomy, which will enhance the usability and safety of automated driving systems by enabling vehicles to perceive, understand, and navigate complex environments.
Requirements
- 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)
Responsibilities
- 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 model improvements
- Contribute to the broader research community through papers, benchmarks, and shared insights
Other
- Based in London
- Hybrid working policy
- Relocation support with visa sponsorship
- Flexible working hours
- Contribute to a diverse, fair and respectful culture that is inclusive of everyone
