VCARB F1 Team-Senior Simulation & Modelling Engineer

Visa Cash App Racing Bulls F1 Team; Faenza; In loco; EUR 50.000 - 70.000; Tempo pieno

Descrizione del lavoro

A leading motorsport team in Italy is seeking a Senior Simulation & Modelling Engineer to lead the development of a Dynamic Lap Simulation tool and vehicle model library. This role demands expertise in vehicle dynamics, control systems, and programming. Join a collaborative, high-performance environment where innovation is key. Competitive compensation and benefits such as an onsite gym and bonus scheme included.

Servizi

Onsite Gym

Bonus scheme

Annual salary review process

Meal Tickets

Free additional health insurance

Competenze

• 5+ years of experience in vehicle dynamics simulation or control system development.
• Deep understanding of vehicle dynamics and control theory.
• Expertise in minimum-lap-time simulation and optimal control methods.
• Strong programming skills in Python, Matlab/Simulink, and C++.

Mansioni

• Lead development of Dynamic Lap Simulation tool.
• Optimize computational performance for simulations.
• Contribute to development of vehicle model library.
• Provide technical expertise and support for simulation projects.

Conoscenze

Vehicle dynamics simulation

Control system development

Numerical optimization

Programming in Python

Programming in Matlab / Simulink

Programming in C++

Formazione

MSc or PhD in Mechanical Engineering, Control Engineering, Applied Mathematics

Strumenti

Modelica (Dymola)

Descrizione del lavoro

Visa Cash App Racing Bulls F1 Team is one of two Red Bull-ownedF1 teams.

Today’s Formula 1 calls for a high level of specialist skills in every area. At Visa Cash App Racing Bulls F1 Team we strongly believe that every member of our staff can and should lead innovation and continuous improvement in such a competitive and dynamic working environment.

Sounds exciting, doesn't? Don't miss your chance to make an impact!

We are looking for an experienced Senior Simulation & Modelling Engineer to be responsible for leading the development of RAB’s Dynamic Lap Simulation tool and related optimal-control-based simulation framework and contributing to the development of RAB’s vehicle model library.

This role is central to the evolution of our in-house performance-simulation capabilities, integrating vehicle & tyre models, control strategies, and using advanced numerical optimization methodologies to feed novel simulation-based methodologies for car performance development and optimization.

Please note that recruitment for this position will take place on a rolling basis, meaning that should the ideal candidate be identified the vacancy will be closed. Should you be interested in the role, we encourage you to promptly apply.

Simulation Framework Development & Optimization

Develop and implement a high-fidelity Dynamic Lap Simulation framework, supporting an optimal-control-based approach to minimum-laptime and parameter optimisation;

Formulate and solve optimal-control problems using advanced numerical techniques (direct/indirect optimisation, collocation, shooting methods, etc.);

Optimise computational performance, ensuring numerical stability, simulation accuracy, and efficient solver integration;

Develop modular, efficient, and scalable codebases, ensuring robustness and maintainability;

Contribute to tool architecture and the development roadmap, defining best practices for simulation methodology, code structure, and validation.

Model Integration & Correlation

Contribute to the development of RAB’s vehicle model library and ensure compatibility with the numerical methods used for dynamic lap simulation;

Correlate simulation outputs with telemetry data to guarantee real-world accuracy and reliability;

Collaborate with Vehicle Dynamics, Aerodynamics, and Tyre Modelling engineers to translate simulation insights into measurable performance improvements;

Technical Leadership & Cross-Functional Support

Ensure that all engineering tools under the role’s ownership meet quality standards and integrate coherently with the VPG Toolset and related guidelines;

Provide technical expertise to support other VPG groups’ simulation-related projects;

Explore innovative solutions for simulation-driven vehicle performance improvement;

Demonstrate flexibility and professionalism in line with project and role requirements, promoting a positive image of the team, department, and sponsors.

What we offer

Working in a young, collaborative and international environment.

Tailored training.

Company Events / Briefings.

Onsite Gym.

Bonus scheme.

Annual salary review process.

Meal Tickets

Free additional health insurance

Experience

• MSc or PhD in Mechanical Engineering, Control Engineering, Applied Mathematics, or related field;
• 5+ years of experience in vehicle dynamics simulation or control system development, ideally in motorsport or high-performance vehicle engineering;
• Deep understanding of vehicle dynamics, control theory, and numerical optimization;
• Expertise in minimum-lap-time simulation, and optimal control methods;
• Relevant experience for the role:
• Dynamic multi-body simulation.
• Model-based control and optimisation.
• Efficient numerical methods implementation (ODEs, nonlinear optimization, collocation method)
• Strong programming skills relevant for the role:
• Python
• Matlab / Simulink
• C++ – efficient simulation and solver implementation
• Modelica (Dymola) – multi-domain physical modelling
• Knowledge of automatic differentiation, code optimisation, and parallel computation techniques would be considered an advantage;
• Driver-in-the-Loop simulation knowledge would be considered an advantage;
• Familiarity with data acquisition and analysis tools and methodologies would be considered an asset;
• Excellent communicative and collaborative skills are essential;
• Excellent problem-solving skills and a proven ability to work under pressure, with a minimum of supervision, to the highest levels of accuracy and quality;
• A flexible approach to working hours is essential, together with a very good knowledge of English.