Machine Learning Engineer, ADAS at Wayve
United Kingdom
Posted
on-site · full-time · Visa sponsorship
Responsibilities:
- Train, debug and optimise computer vision and 3D perception models for ADAS tasks (detection, classification, instance segmentation).
- Own the full ML lifecycle: data collection, labelling, training, evaluation, iteration and deployment.
- Build scalable data pipelines including auto-labelling, pseudo-labelling, tracking and 3D reconstruction to generate high-quality datasets.
- Collaborate with online (in-car) and offline teams to balance latency/compute constraints and dataset scale.
- Define clear evaluation metrics, diagnose failure modes and iterate to close performance gaps.
Requirements:
- 2+ years applied ML engineering experience with production CV-focused deep learning systems (not research-only).
- Practical experience with 3D perception concepts: LiDAR, multi-view geometry, tracking and 3D reconstruction.
- Strong Python skills and familiarity with deep learning frameworks, model training tooling and data pipeline engineering.
- Hands-on, pragmatic problem-solver comfortable owning projects end-to-end under real product constraints.
- Excellent collaboration and communication skills; ability to prioritise work by impact.