Principal Machine Learning Engineer GAIA

Gaia is Wayve's world model: trained on large-scale driving video, it predicts future frames from past context functioning as a simulator that generates synthetic scenarios, and operating in closed loop with the driving model itself. As a Principal ML Engineer/ Applied Scientist, you'll own and drive work on training and improving frontier-scale models trained in-house. This is a high-impact role with the opportunity to tech-lead a key area and help shape the next version of Gaia in a fast-paced, results-focused environment.Key focus areas are getting Gaia stable and coherent over long autoregressive rollouts, and making it reliably steerable towards the behaviours we need using signal from evaluation, and driving-model training.

Key responsibilities

• Lead and execute Gaia's post-training and closed-loop pipeline, fine-tuning and aligning the world model through post-training experimentation and targeted data curation.
• Push Gaia's autoregressive generation towards longer, more stable rollouts, and make the model deployment-ready, inference time and reliability included.
• Contribute to broader model architecture and training-strategy decisions where they intersect with pre- and post-training and the application layer.
• Partner closely with research, applications, simulation engineering, and cloud/infrastructure teams to translate post-training improvements into measurable downstream impact.
• Provide technical leadership through mentorship, review, and setting high engineering/research standards.

About you — Essential

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