Key Notes
ADAS validation spans simulation and physical testing of the Wayve AI Driver, with acceptance criteria agreed across Product, Safety and AV Engineering. The London full-time role combines Python-based evaluation with automotive or autonomous-vehicle experience. A relevant degree appears in the essential criteria, while SOTIF and safety-related validation experience are desirable. The post follows Wayve’s hybrid policy.
What You'll Work On
- Develop validation strategy across simulation and real-world test modalities for ADAS functions.
- Define driving-behaviour metrics, test-coverage requirements and comprehensive validation suites.
- Develop acceptance criteria with Product, Safety and AV Engineering teams.
- Analyse results and report findings to Release and Autonomy Engineering stakeholders.
Why This Role Matters
- ADAS validation combines simulation and physical testing; agreed acceptance criteria and coverage requirements give Release and Autonomy Engineering stakeholders a defined basis for interpreting the results.
- Driving-behaviour metrics turn on-road and simulated test outputs into comparable evidence, supporting assessments of the Wayve AI Driver across the validation programme.
What They Are Looking For
- Experience: Hands-on validation of complex engineered systems, analysing and reporting results, and taking validation concepts through implementation are essential.
- Domain: Automotive or autonomous-vehicle experience appears under essential criteria, although it is repeated under desirable criteria.
- Technical: Python proficiency for metrics and evaluation code is essential.
- Experience: Simulated and physical testing of autonomous systems is essential.
- Qualification: A degree in Computer Science, Robotics, Aerospace or a related field is essential.
- Preferred: ML, computer vision, motion planning, data science, SOTIF/safety validation, learned-behaviour evaluation, AI/agentic tools, SQL or driving-performance measurement experience is desirable.