Machine Learning Engineer, ADAS at Wayve

on-site · full-time · Visa sponsorship

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Responsibilities:
- Train, debug and improve computer vision and 3D perception models (detection, classification, instance segmentation).
- Own the full ML lifecycle: data collection, training, evaluation and iterative improvement.
- Build scalable data pipelines including auto-labelling and pseudo-labelling to accelerate dataset generation.
- Develop offline systems (tracking, 3D reconstruction) to propagate high-quality labels through time.
- Optimize models for online/in-car constraints when required (latency, compute footprint).
- Collaborate with engineers and product teams to prioritize work based on measurable evaluation signals.

Requirements:
- Proven experience shipping CV-focused deep learning systems (applied ML engineering, not research-only).
- Familiarity with 3D perception concepts and pipelines (LiDAR, multi-view geometry, tracking, reconstruction).
- Strong software skills in Python and experience with PyTorch or TensorFlow; C++ is a plus.
- Experience building and evaluating large-scale datasets and labelling pipelines.
- Pragmatic problem-solver who can own projects end-to-end and iterate from metrics and failure cases.
- Effective communicator and collaborator within cross-functional teams.