Aerodynamics AI Internship – Formula 1 Performance Analytics

Paddock; Indianapolis (IN); On-site; USD 30,000 - 42,000; Full time

Job summary

The Cadillac Formula 1 Team in Indianapolis, IN is offering a 12-month Aerodynamics AI Industrial Placement internship. You will join a multidisciplinary data team to develop AI tools for performance analysis, using machine learning on simulation data and technical imagery.

Responsibilities include building models, identifying trends and anomalies, and applying NLP/LLMs to summarize technical information for engineers, with exposure to Python, PyTorch, and modern data frameworks in a fast-paced

Qualifications

• Currently pursuing a degree in a relevant subject such as Computer Science, Engineering, Data Science, or related discipline.
• Strong Python programming skills and clean code practices.
• Solid understanding of machine learning fundamentals.
• Experience in computer vision or NLP with interest in LLMs and information retrieval.

Responsibilities

• Develop machine learning models to analyze technical imagery, simulation outputs, and high-dimensional engineering data.
• Identify trends, differences, and anomalies within complex datasets to support performance analysis.
• Create embedding models and similarity metrics for intelligent data comparison.
• Apply large language models to summarize and synthesize technical information for engineering users.
• Design retrieval-augmented systems using historical engineering and simulation data.

Skills

Python programming

ML fundamentals

Computer vision ML

NLP / LLMs

Clean code practices

Independent collaboration

PyTorch

Multi-modal models

Embeddings / vector DBs

NumPy/SciPy/Pandas

Git / Docker / Linux

Education

Currently pursuing degree in Computer Science, Engineering, Data Science, or related

Tools

Docker

Git

Linux

Job description

The Cadillac Formula 1 Team in Indianapolis, IN is offering a 12-month Aerodynamics AI Industrial Placement internship. You will join a multidisciplinary data team to develop AI tools for performance analysis, using machine learning on simulation data and technical imagery.

Responsibilities include building models, identifying trends and anomalies, and applying NLP/LLMs to summarize technical information for engineers, with exposure to Python, PyTorch, and modern data frameworks in a fast-paced