Aerodynamic AI Engineer

We are looking for an Aerodynamic AI Engineer to join to join the team to leverage data and artificial intelligence to enhance aerodynamic development, performance analysis, and operational efficiency within the Aerodynamics department. This role contributes to the development and execution of the data and AI strategy specifically focused on aerodynamic applications, ensuring that CFD data, wind tunnel measurements, track measurements, and geometric information are transformed into actionable insights through advanced machine learning models and optimization algorithms.

You will be embedded within the Aero Development Team while reporting to the Lead AI Engineer, working on specialized projects that bridge aerodynamic engineering and artificial intelligence. The role will focus on developing cutting-edge AI solutions for aerodynamic data analysis, predictive modelling, and automated geometry generation to support competitive advantage in vehicle development.

Responsibilities:

• Develop and deploy AI models for analysis of CFD simulation data, extracting insights to support aerodynamic development decisions.
• Build advanced surrogate models for aerodynamic predictions, with particular focus on fluid dynamics applications.
• Develop AI-driven mesh generation algorithms and automated geometry creation tools for aerodynamic applications.
• Conduct comprehensive analysis of wind tunnel data, including drift detection, anomaly identification, and statistical analysis to ensure data quality and reliability.
• Build and maintain robust CI/CD pipelines for AI model deployment and ensure high code quality standards across all aerodynamic AI applications.
• Collaborate with aerodynamicists and CFD engineers to translate engineering requirements into AI solutions and communicate complex AI insights in aerodynamic contexts.
• Stay current with emerging AI technologies relevant to computational fluid dynamics and aerodynamic applications.
• Ensure understanding of cost cap requirements and identify AI-driven opportunities to improve aerodynamic development efficiency.

Skills and experienced required:

• Master's or PhD in Engineering, Physics, Computer Science, Mathematics, or related scientific discipline (or equivalent experience).
• Proven experience in developing and deploying AI/machine learning models, particularly for scientific or engineering applications.
• Strong proficiency in Python with PyTorch framework - experience with NVIDIA PhysicsNemo is advantageous.
• Understanding of computational geometry principles and familiarity with mesh generation algorithms.
• Experience with statistical analysis and anomaly detection techniques for large scientific datasets.
• Strong software engineering practices including CI/CD pipeline development and code quality maintenance.
• Knowledge of fluid dynamics concepts and CFD data analysis is advantageous but not essential.
• Excellent communication skills with ability to collaborate effectively with aerodynamicists and translate between technical domains.
• Demonstrated ability to manage multiple projects and deliver results in a fast-paced, high-pressure environment.
• Experience in motorsport, Formula 1, or aerospace aerodynamics is beneficial.

Atlassian Williams Racing is an equal opportunity employer that values diversity and inclusion. We are happy to discuss reasonable job adjustments.