ML Engineer for Synthetic Data & World Models (Hybrid)

Lindus Health; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work policy

London office

Hybrid collaboration culture

Job summary

Wayve is seeking a Machine Learning Engineer to advance world models for autonomous driving. You will bridge research and engineering, post-train GAIA-class models, and scale synthetic data generation for training pipelines.

You will work with researchers and platform engineers to optimize generation, evaluation, and training at scale, in a hybrid London setting with opportunities to push frontier capabilities in AV2.0 contexts.

Qualifications

• 4+ years in applied ML / research engineering, with a track record of training and shipping neural nets.
• Strong Python and PyTorch, comfortable with GPU training, debugging, and reading model code.
• Hands-on experience with video, generative, or world models (diffusion / flow-matching / autoregressive video, etc.).
• Working knowledge of cameras and 3D geometry (multi-camera rigs, intrinsics/extrinsics, warps).
• Experience taking generated data into downstream models and measuring impact.

Responsibilities

• Post-train and iterate world models for synthetic-data capabilities (rig transfer, pose transfer, conditioning).
• Own the generation loop: config → large-scale GPU inference → training-ready artefacts with clear lineage.
• Land synthetic data in driving-model training and related evaluation.
• Diagnose and fix geometry, calibration, and controllability issues that affect training data quality.
• Improve throughput and yield: inference optimisations and self-serve workflows.
• Expand coverage to new vehicle platforms and safety-critical scenarios.
• Collaborate with world-model researchers, infra, and driving-model owners to keep generation, evaluation, and training aligned.

Skills

Python

PyTorch

GPU training

Video models

3D geometry

Collaboration

Research engineering

Tools

PyTorch

Flyte

Ray

Spark

Job description

Wayve is seeking a Machine Learning Engineer to advance world models for autonomous driving. You will bridge research and engineering, post-train GAIA-class models, and scale synthetic data generation for training pipelines.

You will work with researchers and platform engineers to optimize generation, evaluation, and training at scale, in a hybrid London setting with opportunities to push frontier capabilities in AV2.0 contexts.