Machine Learning Engineer - Hybrid in London

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

As a Machine Learning Engineer in the Simulation team, you'll play a key role in developing next-generation world models and planners that can simulate complex, diverse, and temporally consistent driving environments. These generative simulation models (like GAIA) will power faster training, broader testing, and scalable deployment—even in areas and scenarios we've never driven in before.

You'll work at the intersection of machine learning research, multi-modal modeling, and real-world deployment tackling questions like:

• How can we deploy AVs in a new geography without collecting any real-world data?
• Can synthetically generated environments fully replace physical testing and data collection?

Key responsibilities include:

• Inventing next-generation, efficient generative world-models (diffusion, transformer or hybrid) that deliver real-time roll-outs and controllable scene editing.
• Architecting interactive world models where agents (or humans) can step the model, enabling reinforcement learning, planning and safety evaluation loops.
• Optimising end-to-end performance – from latent compression to context pruning your aim is to reduce inference latency by orders of magnitude.
• Integrating your models into closed-loop training and evaluation, and measuring the sim-to-real gap against on-road driving-model results.
• Mentoring and influencing junior researchers, shaping technical road-maps, publishing at top venues and representing Wayve in the community.
• Challenging assumptions and driving innovation: proposing bold ideas, conducting ablation studies, and questioning conventional approaches to training and evaluation.

Requirements:

• 4+ years of experience in ML research/engineering with a focus on generative video, world models.
• Deep knowledge in diffusion & latent-video models; track record of improving sampling efficiency or model throughput.
• Experience working with high-dimensional temporal or spatial-temporal data (e.g., video, multi-sensor fusion).
• Strong Python and PyTorch engineering fundamentals, and experience building research-grade production tools.
• Strong publication record or contributions to open-source ML tooling.

Desirable:

• Experience in AVs, robotics, simulation, or other embodied AI domains.

This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

If you're 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.