Senior ML Engineer: Gaia World Model & Simulation

Wayve; City Of London; Hybrid; GBP 110,000 - 160,000; Full time

Benefits offered by this job

Relocation support

Hybrid working model

Equity / stock options

Learning & conference budget

Health insurance

Job summary

Wayve is seeking a senior AI/ML leader to guide Gaia post-training and closed-loop development in our Simulation team. You will push longer, more stable rollouts, shape model architecture, and partner with Research, Applications, Simulation Engineering and Cloud to deliver measurable improvements.

You will mentor engineers and researchers, drive high-quality implementations, and help ensure latency and reliability targets are met as we scale autonomous driving technologies.

Qualifications

• Hands-on experience post-training / fine-tuning large‑scale models.
• Experience with world models, autoregressive generation and long-horizon generation.
• Strong understanding of model architecture and training decisions.

Responsibilities

• Lead parts of large-scale Gaia training and post-training workflows.
• Influence model architecture and training strategies across teams.
• Mentor teams and uphold high engineering and research standards.
• Collaborate with Research, Applications, Core Simulation Engineering and Cloud/Infrastructure.
• Translate product and evaluation needs into model improvements.

Skills

Post-training / fine-tuning large‑cale

World models

Autoregressive generation

3D vision

PyTorch

Engineering skills

Education

Bachelor's or higher in CS/ML

Tools

PyTorch

Distributed training

Inference optimization

Job description

Wayve is seeking a senior AI/ML leader to guide Gaia post-training and closed-loop development in our Simulation team. You will push longer, more stable rollouts, shape model architecture, and partner with Research, Applications, Simulation Engineering and Cloud to deliver measurable improvements.

You will mentor engineers and researchers, drive high-quality implementations, and help ensure latency and reliability targets are met as we scale autonomous driving technologies.