Senior ML Engineer: Scalable Synthetic Data for Autonomous Driving

OpenDigital Limited; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Wayve in London is seeking an experienced ML Engineer (MLE) to build and scale world-model architectures and synthetic-data pipelines. You will bridge ML research and engineering, collaborating with scientists and platform engineers to produce training artefacts and data for autonomy development.

The role is full-time and based in our London office with a hybrid policy that combines office and home working to fuel innovation and collaboration.

Qualifications

• 4+ years in applied ML / research engineering.
• Strong Python and PyTorch; GPU training experience.
• Hands-on with video, generative, or world models.
• Knowledge of cameras and 3D geometry for robust generation.
• Evidence of using generated data to improve downstream models.
• Ability to run multi-GPU training at scale with reliable workflows.
• Collaborative, experimental mindset; own a capability.

Responsibilities

• Post-train GAIA-class world models for synthetic-data capabilities: rig transfer, pose transfer, and conditioning.
• Own the generation loop: config → large-scale GPU inference → training-ready artefacts.
• Land synthetic data in driving-model training with mixing, quality checks, and experiments.
• Diagnose geometry, calibration, and controllability failures affecting training data.
• Improve throughput: inference optimisations and self-serve workflows for model developers.
• Expand coverage to new vehicle platforms and safety-critical scenarios.
• Partner with world-model researchers, infra, and driving-model owners to keep systems unified.

Skills

Python

PyTorch

ML research

Video models

3D geometry

Multi-GPU training

Collaboration

Tools

Flyte

Ray

Spark

Job description

Wayve in London is seeking an experienced ML Engineer (MLE) to build and scale world-model architectures and synthetic-data pipelines. You will bridge ML research and engineering, collaborating with scientists and platform engineers to produce training artefacts and data for autonomy development.

The role is full-time and based in our London office with a hybrid policy that combines office and home working to fuel innovation and collaboration.