Principal Machine Learning Engineer GAIA

Overview

In this role you will lead and shape Gaia, Wayve’s world model, by advancing post-training and closed-loop pipelines for frontier-scale models. You will drive longer, stable autoregressive rollouts and ensure deployment-ready performance, working across research, simulation, and cloud teams. You’ll mentor teams and set high engineering and research standards while contributing to architectural decisions. This position offers impact through cross-functional collaboration and direct influence on Gaia’s next version in a fast-paced, outcomes-driven environment.

Responsibilities

• Lead Gaia post-training and closed-loop pipeline enhancements, including data curation and fine-tuning
• Extend autoregressive generation to longer, more stable rollouts and ensure deployment-ready inference
• Contribute to model architecture and training strategy decisions across pre/post-training layers
• Collaborate with research, simulation engineering, and cloud/infrastructure teams to translate improvements into measurable downstream impact
• Provide technical leadership through mentorship, code reviews, and setting high standards

Key requirements

• Hands-on experience post-training/fine-tuning large-scale models (language, video, or other foundation models)
• Experience with world models, autoregressive generation, and long-horizon generation
• Experience with diffusion/flow models and understanding of 3D vision
• Strong understanding of model architecture and ability to contribute to architectural/training decisions
• Strong hands-on engineering skills with modern ML stacks (e.g., PyTorch) including debugging and reliability-minded development
• Relevant industry experience (typically 5+ years) or equivalent depth of applied experience
• Advanced degrees valued but not required

• technical leadership
• mentorship
• cross-functional collaboration
• world models
• autoregressive generation
• diffusion/flow models

…