Applied Scientist, Wayve Labs

The Role

Were looking for Applied Scientists to join Wayve Labs and help build the next generation of AI systems for autonomous driving. Youll work at the intersection of machine learning, simulation, robotics, and real-world deployment, contributing to core innovations that push the boundaries of embodied AI.

Situated within Wayve, we are a high-conviction research team with the strategic patience and backing to prioritise multi-year breakthroughs over incremental gains. We are looking for highly motivated individuals with expertise and passion to push the frontier of embodied AI, including (but not limited to) the following areas:

World & Reward Modeling: Building realistic, diverse simulators that can predict the consequences and costs of actions.

Representation Learning & Spatial Intelligence: Advancing how machines truly understand and navigate dynamic, unstructured 3D environments, from detailed spatial understanding, to efficient long term memory.

Scalable Decision-Making Systems: Designing architectures, reasoning systems, and policy learning algorithms that operate over long contexts, and scale with data and compute.

Cross-Embodiment and Multimodal Learning: Advance embodied learning systems that can flexibly adapt to diverse robotic platforms and multimodal inputs, using vision, language, and active sensors.

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
• Develop Geometric Foundation Modelsfor 3D spatial understanding in dynamic, real-world environments.
• 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

What Youll Bring

Must-haves:

• 3+ years of experience developing and deploying ML systems in real-world or production settings
• PhD, Masters 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 >Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.
  

  We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If youre passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.
  
  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, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

  For more information visit Careers at Wayve.

  To learn more about what drives us, visit Values at Wayve

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  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.