Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

Gaia is Wayve’s video world model, functioning as a simulator that predicts future frames from past context. As a Staff ML Engineer on Gaia, you will 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.

Responsibilities

• Lead and execute large-scale training runs for video (or adjacent) foundation models, from experimental design through production-grade execution.
• Contribute to model architecture and training strategy, using first-principles understanding rather than “off-the-shelf” application.
• Improve world-model capabilities that enable synthetic scenario generation and downstream evaluation/training of the driving model.
• Partner closely with research, applications, simulation engineering, and cloud/infrastructure teams to deliver end-to-end impact.
• Provide technical leadership through mentorship, review, and setting high engineering/research standards (Senior/Staff scope).

Requirements

• In-depth experience training large-scale models (language, video, or other foundation models), including ownership of training at scale.
• Strong understanding of model architecture and the ability to contribute meaningfully to architectural/training decisions.
• Strong hands-on engineering skills with modern ML stacks (e.g., PyTorch), including debugging and performance/reliability-minded development.
• Relevant industry experience (typically 4–5+ years); advanced degrees are valued, but depth of applied experience is important.
• Direct experience with world models, video generation, or long-horizon prediction.
• Experience improving data/training pipelines and working across infrastructure constraints (distributed training, efficiency, reliability).
• Proven technical leadership (tech lead ownership, mentoring, setting direction across an area).

Skills

• PyTorch

Location

• London

Work Type

• Full-time
• Hybrid

Experience Level

• Staff
• Senior
• 4-5+ years

Education Level

• Advanced degrees valued