Machine Learning Engineer, Synthetic Data

📋 Description

• Post-train, distill, and evaluate GAIA-family large video diffusion models to improve generation
• Build and run synthetic video generation pipelines across tens of thousands of driving segments.
• Integrate synthetic data across different stages of driving-model training, develop sampling
• Work with driving-model teams to determine effective data mixtures and with simulation and
• Translate advances in world modelling, video generation, flow matching, distillation, and
• Post-train and iterate GAIA-class world models for synthetic-data capabilities: embodiment transfer

🎯 Requirements

• 4+ years in applied ML / research engineering, with a track record of training and shipping neural
• Strong Python and PyTorch (or equivalent); comfort with GPU training, debugging, and reading model
• Hands-on experience with video, generative, or world models (diffusion / flow-matching /
• Working knowledge of cameras and 3D geometry (multi-camera rigs, intrinsics/extrinsics
• Evidence of taking generated or simulated data into a trained downstream model and measuring impact
• Ability to operate generation or training at real scale (multi-GPU jobs, workflow orchestration

🎁 Benefits

• Salaries benchmarked against the market annually
• Meaningful equity, sharing in the ownership and long term success of Wayve
• Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
• Learning and development budgets with support for training, conferences and growth
• Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave