TL;DR

Machine Learning Engineer (AI): Developing the next generation of generative world models (GAIA) that simulate the world with unprecedented fidelity and generalization with an accent on generative modeling, simulation, and reinforcement learning. Focus on designing controllable models that allow agents to play, explore, and learn safely, enabling faster training, broader testing, and scalable deployment.

Location: Sunnyvale, California USA

Company

Wayve is the leading developer of Embodied AI technology, creating advanced AI software and foundation models to enable vehicles to perceive, understand, and navigate any complex environment.

What you will do

  • 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.

Culture & Benefits

  • 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.