12-Month Aerodynamics AI Industrial Placement
Silverstone, England, United Kingdom
The Cadillac Formula 1® Team is what happens when history, purpose and daring talent come together. Backed by TWG Global and GM, our team is uniquely positioned to disrupt Formula 1®, bringing a fresh perspective and an unrelenting drive for success.
Building the car is just the start. We're building a global brand and a legacy that will shape the future of motorsports. At the core of our ambition is a high-performance environment for our people, driven by bold ambition, leadership in innovation, excellence in execution. We are one team. For those who want to dare and dream, make and craft, create a legacy that lasts. A historic name behind us. Career-defining moments ahead.
For those who want to feel unstoppable. This one's for you.
Closing Date: Friday 30th October 2026
Fueled by bold ambition
More about the opportunity
We have an exciting opportunity for a Machine Learning / AI Industrial Placement student to join a Formula 1® team working at the forefront of performance-driven engineering. Formula 1® generates vast quantities of technical, simulation, and operational data each week, and transforming this data into actionable insight is critical to on-track performance.
As part of a multidisciplinary engineering and data team, you will work closely with engineers and domain experts to develop next-generation AI tools that support performance development. This placement offers a unique opportunity to apply cutting-edge machine learning techniques directly within a Formula 1® environment and contribute to tools used in real engineering decision-making.
- Developing machine learning models to analyse technical imagery, simulation outputs, and high-dimensional engineering data
- Identifying trends, differences, and anomalies within complex datasets to support performance analysis
- Creating embedding models and similarity metrics to enable intelligent comparison of engineering data
- Applying large language models (LLMs) to summarise and synthesise technical information for engineering users
- Designing retrieval-augmented systems using historical engineering and simulation data
- Building internal tools and interfaces to support engineers in extracting insight from data
- Deploying and testing prototype systems locally using modern software frameworks
- Working closely with domain experts to guide model development and interpret outputs
REQUIREMENTS
What do we need from you?
- Currently studying for a degree in a relevant subject such as Computer Science, Engineering, Data Science, or a related discipline
- Strong Python programming skills
- Solid understanding of machine learning fundamentals
- Experience in at least one of the following areas:
- Computer vision or image-based machine learning
- Natural language processing, LLMs, or information retrieval systems
- Ability to write clean, well-structured, and well-documented code
- Proactive mindset, curiosity, and the ability to work independently while collaborating with others
Desirable Skills
- Experience with deep learning frameworks (PyTorch preferred)
- Exposure to multi-modal models combining vision and language
- Familiarity with embedding techniques and vector databases
- Interest in engineering, simulation, or data-driven performance analysis
- Experience with scientific Python libraries (NumPy, SciPy, Pandas)
- Familiarity with Git version control, Docker, and Linux-based environments