AI/ML Industrial Placement: Formula 1 Aerodynamics

Motorsport Network, LLC; Indianapolis (IN); On-site; USD 28,000 - 41,000; Full time

Job summary

The Cadillac Formula 1 Team invites a machine learning/AI industrial placement student to join our data and engineering team. You will help transform vast technical and simulation data into actionable insights that guide performance decisions on the track.

You will build ML models for imagery and simulations, explore embeddings, and apply LLMs to summarize complex engineering information for engineers. This is a hands-on, collaborative role within a Formula 1 environment.

Qualifications

• Pursuing a degree in CS/Engineering/Data Science or related field.
• Strong Python programming skills and ML fundamentals.
• Experience in CV, NLP, or information retrieval is a plus.
• Ability to write clean, well-documented code.
• Independent, proactive mindset with collaborative spirit.

Responsibilities

• Develop ML models for technical imagery, simulations, and high-dimensional data.
• Identify trends, differences, and anomalies in complex datasets.
• Create embedding models and similarity metrics for engineering data.
• Apply LLMs to summarize and synthesize technical information for engineers.
• Design retrieval-augmented systems using historical data.
• Build internal tools and interfaces for engineers to extract insights.
• Deploy and test prototype systems locally using modern frameworks.
• Collaborate with domain experts to guide model development.

Skills

Python

ML fundamentals

Clean code

Independent yet collaborative

Education

CS/Engineering/Data Science degree (in progress)

Tools

PyTorch

Git

Docker

Linux

Job description

The Cadillac Formula 1 Team invites a machine learning/AI industrial placement student to join our data and engineering team. You will help transform vast technical and simulation data into actionable insights that guide performance decisions on the track.

You will build ML models for imagery and simulations, explore embeddings, and apply LLMs to summarize complex engineering information for engineers. This is a hands-on, collaborative role within a Formula 1 environment.