Aerodynamic AI Engineer

Atlassian Williams F1 Team; Grove; On-site; GBP 70,000 - 110,000; Full time

Job summary

Atlassian Williams F1 Team seeks an Aerodynamic AI Engineer to bridge aerodynamic engineering and AI. You will develop ML models for CFD data analysis, build surrogate models, and automate geometry tools to accelerate vehicle development.

You will collaborate with aerodynamicists and CFD engineers, translating complex requirements into robust AI solutions while maintaining high-quality code and CI/CD practices in a fast-paced F1 environment.

Qualifications

• Proven experience developing and deploying AI/ML models for scientific or engineering applications.
• Strong proficiency in Python with PyTorch.
• Understanding of computational geometry & mesh generation.
• Experience with statistical analysis and anomaly detection on large datasets.
• CI/CD pipelines & code-quality practices.
• Excellent communication across technical disciplines.
• Ability to manage multiple projects in a fast-paced environment.
• Master's or PhD in a relevant scientific field (or equivalent experience).

Responsibilities

• Develop and deploy AI models for aerodynamic data analysis.
• Build surrogate models for predictions in CFD contexts.
• Create AI-driven mesh generation and geometry tools.
• Analyze wind tunnel/CFD data for quality and insights.
• Maintain CI/CD pipelines for AI models in production.
• Collaborate with aerodynamicists and CFD engineers to translate requirements.

Skills

AI/ML for engineering

Python (PyTorch)

Computational geometry

Mesh generation

Anomaly detection

CI/CD pipelines

Cross-disciplinary communication

Project management

Education

Master's or PhD (Engineering/Physics/CS/Math)

Job description

THE ROLE

The Aerodynamic AI Engineer is part of a dedicated team leveraging data and artificial intelligence to enhance aerodynamic development, performance analysis, and operational efficiency within the Aerodynamics department. Reporting to the Lead AI Engineer, you will work on specialist projects that bridge aerodynamic engineering and AI developing advanced machine learning models, surrogate models, and automated geometry tools that give Williams Racing a competitive edge in vehicle development. This is a technically demanding, hands-on role in a fast-paced, high-pressure environment. You will collaborate closely with aerodynamicists and CFD engineers, translating complex engineering requirements into practical AI solutions and communicating your findings with clarity and impact.

What You’ll Do

• Develop and deploy AI models for the analysis of CFD simulation data, extracting insights to support aerodynamic development decisions.
• Build advanced surrogate models for aerodynamic predictions, with a 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, ensuring 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 insights effectively.
• Stay current with emerging AI technologies relevant to computational fluid dynamics and aerodynamic applications.
• Identify AI-driven opportunities to improve aerodynamic development efficiency within cost cap requirements.

Company Description

For almost 50 years, Williams has been at the forefront of one of the fastest sports on the planet, being one of the top three most successful teams in history competing in the FIA Formula 1 World Championship. With an almost unrivalled heritage of engineering and racing F1 cars and unforgettable eras that demonstrate it is a force to be reckoned with, the British squad boasts 16 F1 World Championship titles to its name.

Since its foundation in 1977 by the eminent, late Sir Frank Williams and engineering pioneer Sir Patrick Head, the team has won nine Constructors’ Championships, in association with Cosworth, Honda and Renault. Its roll call of drivers is legendary, with its seven Drivers’ Championship trophies being lifted by true icons of the sport: Alan Jones, Keke Rosberg, Nelson Piquet, Nigel Mansell, Alain Prost, Damon Hill and Jacques Villeneuve. The team has made history before and is out to make it again with a long-term mission to evolve and return to the front of the grid.

Qualifications

SKILLS & EXPERIENCE

Essential

• Proven experience developing and deploying AI/ML models, particularly for scientific or engineering applications.
• Strong proficiency in Python with the PyTorch framework.
• 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 standards.
• Excellent communication skills, with the ability to collaborate across technical disciplines and translate complex AI concepts for engineering audiences.
• Demonstrated ability to manage multiple projects and deliver results in a fast-paced, high-pressure environment.
• Master's or PhD in Engineering, Physics, Computer Science, Mathematics, or a related scientific discipline (or equivalent practical experience).

Desirable

• Experience with NVIDIA PhysicsNemo or similar physics-informed machine learning frameworks.
• Knowledge of fluid dynamics concepts and CFD data analysis.
• Experience in motorsport, Formula 1, or aerospace aerodynamics.

Additional Information

Atlassian Williams F1 Team is an equal opportunity employer that values diversity and inclusion. We are happy to discuss reasonable job adjustments.