Wayve is looking to hire Applied Scientists to join their Science team to build the next generation of AI systems for autonomous driving. The role involves working at the intersection of machine learning, simulation, robotics, and real-world deployment to contribute to core innovations that push the boundaries of embodied AI.
Requirements
- Deep expertise in one or more of the following: Foundation model development (e.g., Transformers, MoE, large-scale training)
- Generative world modeling (e.g., autoregressive, diffusion, hybrid models)
- Reinforcement learning, including offline RL, RLHF, reward modeling
- Spatial AI, including transformer-based techniques for SFM/SLAM, depth estimation and multi-view geometry, making use of multimodal (RGB, LIDAR, RADAR, IMU) sensors.
- Other related areas of Machine Learning.
- Strong programming skills in Python and experience with PyTorch or equivalent ML frameworks
- Familiarity with training at scale (e.g., FSDP, DeepSpeed, JAX)
Responsibilities
- Design and train large-scale embodied foundation models, advancing architectures in attention, mixture-of-experts, and distributed training.
- Develop world models and planners (e.g., diffusion, transformer-based, or hybrid generative approaches) to simulate diverse and temporally consistent driving environments.
- Innovate in reinforcement learning and reward modeling, building safe, efficient, and scalable reward frameworks integrated with real-world and synthetic data.
- Conduct empirical research on scaling laws, generalisation, and synthetic-to-real transfer for autonomous systems.
- Define benchmarks and metrics for long-horizon prediction, scene fidelity, planner integration, and driving performance.
Other
- PhD, Master’s degree, or equivalent experience in Machine Learning, Computer Vision, Robotics, or related fields
- Applicants should have a minimum of 4 years’ experience in applied ML research or engineering.
- Track record of publishing at top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
- Strong problem-solving ability, collaboration mindset, and ability to thrive in a fast-paced, interdisciplinary team
- Experience in autonomous driving, robotics, or simulation
