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Wayve is building an AI platform for autonomous driving using end-to-end learning from real-world experience. The Vehicle Modelling team develops virtual vehicle models that improve simulation accuracy and driving performance across the company.
In this role, you will develop virtual vehicle models using physics-based and data-driven techniques, validating them against on-road data and implementing correlation improvements. You'll convert models into efficient, high-quality software components meeting accuracy, performance, and scalability requirements. Your responsibilities include planning and running experimental tests at tracks or with external partners to improve model accuracy, and sharing results with stakeholders across robotics, simulation, and product teams.
Key projects include building virtual vehicle models integrated with advanced modelling technologies for simulation and evaluation; defining metrics and KPIs for representative simulations; integrating models across Wayve's simulation, hardware-in-the-loop, and correlation pipelines; and conducting cross-functional vehicle characterisation work. As the team scales, there is room to specialise in pure modelling, correlation/metrics, or experimental track work.
Wayve operates a hybrid model with main hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg, combining in-person collaboration with remote flexibility. The company offers competitive salaries, meaningful equity, relocation support and visa sponsorship, learning and development budgets, comprehensive benefits including health insurance, dental, enhanced parental leave, and retirement/pension plans.
REQUIREMENTS:
- Experience developing mathematical models and simulation algorithms for vehicle dynamics, robotics, or control systems
- Strong grasp of classical mechanics, numerical analysis, and computational methods
- Demonstrated validation of simulation models against experimental data with understanding of acceptable accuracy thresholds
- Production-quality code proficiency in C++ or Python
- Previous experience in vehicle dynamics for autonomous vehicles, automotive, or motorsport
- Comfort with data-driven approaches such as machine learning or system identification for modelling systems with unknown physical parameters
- Familiarity with high-fidelity vehicle dynamics tools (e.g., Dymola, CarSim, CarMaker) and integration into simulation workflows
Note: The posting encourages applications from those passionate about autonomy even if not meeting every requirement.
