Machine Learning Engineer (Synthetic Data)

📋 Description

• Role focuses on world models and synthetic data for autonomous driving research.
• Build, scale, and optimise GAIA-class architectures and data generation pipelines.
• Bridge ML research with engineering for high-throughput generation and training.
• Post-train world models for new embodiments and behaviours.
• Improve throughput, yield, and self-serve synthetic data workflows.

🎯 Requirements

• 4+ years in applied ML / research engineering
• Strong Python and PyTorch; GPU training and debugging
• Hands-on with video, generative, or world models
• Knowledge of cameras and 3D geometry
• Experience using generated data in training and measuring impact
• Ability to run generation/training at scale (multi-GPU)

🎁 Benefits

• Hybrid work policy with London office time
• Core working hours to suit you and your team
• Culture focused on autonomy and high-trust teams