Autonomous Vehicle Dynamics Engineer

Wayve; London (KY); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Health insurance

Dental plan

Job summary

Wayve is seeking a Vehicle Performance Modelling Engineer to develop physics-based and data-driven vehicle models, integrate them into the end-to-end driving stack, and validate accuracy through on-road and simulated testing.

The role involves collaborating with robotics, simulation, and product teams to shape the future of autonomous driving and improve model performance across online and offline systems.

Qualifications

• Experience in developing mathematical models and simulation algorithms for vehicle dynamics, robotics or control systems.
• Understanding of classical mechanics, numerical analysis and computational methods.
• Experience in validating simulation models against experimental data.
• Software development with C++ or Python.

Responsibilities

• Develop virtual vehicle models using physics-based and data-driven techniques.
• Create detailed models that represent vehicle and subsystems virtually.
• Validate models with on-road data and identify correlation improvements.
• Convert models into efficient software components meeting accuracy, performance and scalability requirements.
• Own processes, tools and experiments to evaluate on-road vehicle performance metrics.
• Plan, execute and analyse experimental tests to improve models accuracy.
• Share results and insights with stakeholders to foster collaboration and drive innovation.

Skills

Vehicle dynamics modelling

Mathematical modelling

Simulation algorithms

C++ or Python

Data validation

Tools

Dymola

CarSim

Python

C++

Job description

Wayve is seeking a Vehicle Performance Modelling Engineer to develop physics-based and data-driven vehicle models, integrate them into the end-to-end driving stack, and validate accuracy through on-road and simulated testing.

The role involves collaborating with robotics, simulation, and product teams to shape the future of autonomous driving and improve model performance across online and offline systems.