Applied Scientist/Machine Learning Engineer Gaia

📋 Job Overview

Generative simulation is the team that is advancing our end-to-end autonomous driving research. The team’s mission is to accelerate our journey to AV2.0 and ensure the future success of Wayve by incubating and investing in new ideas that have the potential to become game-changing technological advances for the company.

🏢 About Wayve

Wayve is a leading company in autonomous driving technology, focusing on transformative innovations that impact mobility, safety, and AI.

🎯 The Role

This role would sit within Simulation focusing on unlocking disruptive innovation that solves self-driving. We believe the next leap in autonomy comes from a world model that is faithful enough, and fast enough, to train and evaluate driving models in closed loop — not only to replay logs. 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.

✅ Key Responsibilities

• Invent next-generation, efficient generative world-models (diffusion, transformer or hybrid) that deliver real-time roll-outs and controllable scene editing.
• Architect interactive world models where agents (or humans) can step the model, enabling reinforcement learning, planning and safety evaluation loops.
• Optimise end-to-end performance – from latent compression to context pruning your aim is to reduce inference latency by orders of magnitude.
• Define robust metrics for long-horizon coherence, physics fidelity and planner integration; run ablations and scaling studies to understand trade-offs.
• Ship impact: integrate your models into closed-loop training and evaluation, and measure the sim-to-real gap against on-road driving-model results.
• Mentor & influence: guide junior researchers, shape technical road-maps, publish at top venues and represent Wayve in the community
• Challenge assumptions and drive innovation: propose bold ideas, conduct ablation studies, and question conventional approaches to training and evaluation.

📌 Required Qualifications

• 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.
• Ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment.

⭐ Desirable Experience

• Experience in AVs, robotics, simulation, or other embodied AI domains.
• Experience working with synthetic-to-real transfer.

🎁 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.

🛂 Visa & Eligibility

This is a full-time role based in our office in London or Sunnyvale. 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. We operate core working hours so you can determine the schedule that works best for you and your team.