Research Scientist, Wayve Labs

About the role

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. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.

Key Responsibilities

• Develop World Models and Planners (e.g., diffusion-based, autoregressive, or hybrid approaches) for realistic and consistent simulation
• Advance Reinforcement Learning and Reward Modeling, building scalable and safe learning frameworks across real and synthetic data
• Enable Cross-Embodiment Robotics, leveraging the power of multimodal foundation models to accelerate robotic learning on diverse platforms
• Conduct empirical research on Scaling laws, Generalisation, and Sim-to-real transfer
• Define and evolve Evaluation Frameworks and Benchmarks for long-horizon prediction, scene fidelity, and driving performance

Must-haves

• 3+ years of experience developing and deploying ML systems in real-world or production settings
• PhD, Master’s degree, or equivalent experience in Machine Learning, Computer Vision, Robotics, or a related field
• Deep expertise in one or more core Embodied AI areas, such as: Foundation models (e.g., transformers, MoE, large-scale training), Generative world modeling (e.g., diffusion, autoregressive, hybrid approaches), Reinforcement learning (e.g., offline RL, RLHF, reward modeling), Spatial AI (e.g., SLAM/SfM, depth estimation, multi-view geometry with multimodal sensors)
• Track record of publications at top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
• Strong programming skills in Python, with experience using frameworks such as PyTorch
• A data-centric mindset, with experience working on large-scale datasets and evaluation
• Strong problem-solving ability and the ability to collaborate effectively in interdisciplinary teams

Nice-to-haves

• Experience in autonomous driving, robotics, or simulation systems
• Familiarity with large-scale training (e.g., FSDP, DeepSpeed, JAX)
• Experience with sim-to-real transfer or data-efficient learning
• Contributions to open-source ML tools or research infrastructure

What We Offer

• Athletic Chef
• Workplace Nursery Scheme
• Private Health Insurance
• Therapy
• Daily Yoga
• Onsite Bar
• Large Social Budgets
• Unlimited L&D Requests
• Enhanced Parental Leave

Benefits

• Relocation Support with Visa Sponsorship
• Flexible Working Hours

Actual Compensation

The reasonably estimated salary for this role ranges from $230,000 to $380,000, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.

Disclaimer

We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.