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This role would sit within Science focusing on unlocking disruptive innovation that solves self-driving. We believe the next leap in autonomy won’t come from collecting endless real-world miles — it will come from simulating the world with unprecedented fidelity and generalisation. That’s where GAIA, our generative world model, comes in. As an Applied Scientist on the Science team, you’ll play a central role in developing the next generation of GAIA. These controllable world models will roll out diverse, photoreal, and physics-aware futures across multiple sensors (camera, radar, LiDAR), powering faster training, broader testing, and scalable deployment — even in places and situations we’ve never driven before.
Job Responsibility:
Invent next-generation generative world models (diffusion, transformer, or hybrid) that deliver real-time, controllable rollouts
Architect controllable GAIA models where agents can step into the world, enabling reinforcement learning, planning, and safety evaluation
Define robust metrics for long-horizon coherence, physics fidelity, and planner integration
run ablations and scaling studies to understand trade-offs
Ship impact by integrating models with fleet-scale training, sim-to-real evaluation, and on-vehicle deployment
Mentor & influence: guide junior researchers, shape technical roadmaps, publish at top venues, and represent Wayve in the global research community
Challenge assumptions: propose bold ideas, run disruptive experiments, and question conventional approaches
Requirements:
Expertise in ML research/engineering with a focus on generative video, world models
Deep knowledge in diffusion & latent-video models
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
Ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment
Nice to have:
Experience in AVs, robotics, simulation, or other embodied AI domains
Experience working with synthetic-to-real transfer
What we offer:
Work on transformative technology with real-world impact on mobility, safety, and AI
Access massive driving datasets, cutting-edge infrastructure, and world-class research talent
Be part of a high-trust, high-autonomy team that values creativity, experimentation, and deep thinking
Publish, share, and shape the future of generative AI for autonomy