1 day ago
London, United KingdomSenior
Responsibilities
- Invent efficient generative world models using diffusion, transformer, or hybrid architectures for real-time rollouts and controllable scene editing.
- Architect interactive world models that support reinforcement learning, planning, and safety evaluation loops.
- Optimize end-to-end inference performance, including latent compression and context pruning, to reduce latency substantially.
- Define metrics for long-horizon coherence, physics fidelity, and planner integration, and conduct ablation and scaling studies.
- Integrate models into closed-loop training and evaluation and measure the sim-to-real gap against on-road driving-model results.
- Mentor junior researchers, influence technical roadmaps, publish at leading venues, and represent Wayve in the research community.
Requirements
- At least 4 years of ML research or engineering experience focused on generative video or world models.
- Deep knowledge of diffusion and latent-video models, with experience improving sampling efficiency or model throughput.
- Experience working with high-dimensional temporal or spatiotemporal data such as video or multisensor fusion.
- Strong Python and PyTorch engineering fundamentals and experience building research-grade production tools.
- A strong publication record or contributions to open-source machine learning tooling.
- Ability to collaborate effectively in a fast-paced, innovative, interdisciplinary environment.
- Experience in autonomous vehicles, robotics, simulation, or embodied AI is desirable.
- Experience with synthetic-to-real transfer is desirable.
Benefits
- Full-time role based in Wayve’s London office.
- Hybrid working policy combining office and workshop collaboration with work from home.
- Core working hours with flexibility to determine a suitable schedule.
- Opportunity to work on mobility, safety, autonomous driving, and generative AI technology with access to large driving datasets and advanced infrastructure.
- High-trust, high-autonomy environment with opportunities to publish, share work, and collaborate with leading research talent.
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