Aerodynamic AI Engineer

Overview

In this role you apply AI to aerodynamic development, working with CFD data, surrogate models, and automated geometry tools to give Williams Racing a competitive edge. You will collaborate with aerodynamicists and CFD engineers to translate complex requirements into practical AI solutions. The role combines science and engineering in a fast-paced, high-pressure environment with a focus on data-driven decision making. You will stay at the forefront of AI for CFD and contribute to efficiency within cost cap constraints.

Responsibilities

• Develop and deploy AI models for CFD data analysis to support aerodynamic decisions
• Create surrogate models for aerodynamic predictions, emphasizing fluid dynamics
• Develop AI-driven mesh generation and automated geometry tools for aerodynamics
• Analyze wind tunnel data, including drift detection and anomaly identification
• Build and maintain CI/CD pipelines for AI model deployment and ensure code quality
• Collaborate with aerodynamicists and CFD engineers to translate requirements into AI solutions
• Keep up-to-date with AI tech relevant to CFD and aerodynamics
• Identify opportunities to improve aerodynamic development efficiency under cost cap requirements

Key requirements

• Proven experience developing and deploying AI/ML models for scientific or engineering applications
• Strong Python proficiency with PyTorch
• Understanding of computational geometry and mesh generation algorithms
• Experience with statistical analysis and anomaly detection on large scientific datasets
• Strong software engineering practices including CI/CD and code quality
• Excellent communication and cross-disciplinary collaboration skills
• Ability to manage multiple projects in a fast-paced environment
• Master’s or PhD in a related scientific discipline (or equivalent practical experience)

• Excellent communication
• Cross-functional collaboration
• Project management under pressure
• Python
• PyTorch
• Computational geometry

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