Your Responsibilities

• Process and analyze large-scale time-series data from vehicle sensors using advanced signal processing techniques (time and frequency domain).
• Develop data-driven and physics-based simulation models to estimate vehicle component wear (especially tire and brake).
• Design, implement and optimize numerical and control-oriented models for vehicle dynamics applications using model-based development approaches.
• Translate simulation and control models into production-ready functions and support their deployment on embedded systems (ECUs), including code generation and integration.
• Work with Python and/or MATLAB/Simulink for data analysis, modeling, auto-code generation, and model validation.
• Manage deployment for customers as well as core development and research.
• Collaborate with cross-functional teams, including data scientists and software engineers, to integrate developed models and functions into automotive software architectures.

Your profile

• 8+ years of experience in physical modelling and system-based approaches for vehicle dynamics, motion control, or ADAS.
• Strong understanding of vehicle dynamics, control systems, and signal processing.
• Hands-on experience in model-based development (e.g. MATLAB/Simulink) and transformation of models into embedded software functions.
• Experience with deployment and integration of functions on embedded systems (ECUs), including code generation workflows.
• Degree in electronics, mechatronics, mechanical engineering, or a related field.
• Experience with MATLAB/Simulink is required; Python or C code is a strong plus.
• Knowledge of machine learning concepts is an advantage. Previous experience in ASPICE development is a plus.
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