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Wayve is building an AI platform for autonomous driving using end-to-end learning approaches. The ADAS (Advanced Driver Assistance Systems) engineering team develops perception and intelligence systems that power driver assistance in real-world driving scenarios.
In this role, you will train, debug, and improve computer vision and 3D perception models that enable vehicles to understand and navigate complex urban environments. You'll work across the full ML lifecycle—from data creation and pipeline development to model training, evaluation, and iteration based on clear performance signals.
Key responsibilities include:
- Developing core ADAS perception capabilities such as detection, classification, and instance segmentation for lanes, objects, traffic signs, and traffic lights
- Building end-to-end approaches that allow models to act directly on the world rather than relying on hand-coded intermediate steps
- Creating online perception systems that run efficiently in-car as part of the production stack
- Developing offline perception work using additional sensors (lidar, future frames, maps) and compute to improve data quality and coverage at scale
- Building data flywheels using offline models and 3D tracking/reconstruction to auto-generate labels and accelerate iteration
- Partnering with the team to prioritize work based on system performance gaps
- Building scalable data pipelines including auto-labelling and pseudo-labelling
Wayve operates a hybrid model with main hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg. The company offers competitive salaries benchmarked to market, meaningful equity, relocation support and visa sponsorship, learning and development budgets, comprehensive benefits including health insurance, dental, enhanced parental leave, retirement/pension, and access to wellbeing services.
The interview process includes a recruiter screen (30 mins), competency interviews on programming and system design (2 hours), a deep-dive technical interview with hiring manager (1 hour), and a final mission & values alignment interview (1 hour).
REQUIREMENTS:
- Built and shipped computer vision-focused deep learning systems with strong applied ML engineering (not research-only)
- Experience with 3D perception concepts or pipelines such as LiDAR, multi-view geometry, tracking, or 3D reconstruction
- Comfortable owning work end-to-end, including evaluation and large-scale dataset generation
- Pragmatic problem-solving approach under real product constraints
- Passion for improving real-world driving performance through better perception
- Automotive domain experience is a bonus but not required if perception background is strong from other domains
- The company encourages applications from those passionate about autonomy even if not meeting every requirement
