12-Month Aerodynamics AI Industrial Placement (US)

Paddock; Indianapolis (IN); Vor Ort; USD 30.000 - 42.000; Vollzeit

Zusammenfassung

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

Qualifikationen

• 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.

Aufgaben

• 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.

Kenntnisse

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

Ausbildung

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

Tools

Docker

Git

Linux

Jobbeschreibung

Cadillac Formula 1 Teamcadillacf1team.comStudents & graduates · Indianapolis, Indiana, United States# 12-Month Aerodynamics AI Industrial Placement (US)Internship**Closing Date**Friday 6th November 2026Fueled by bold ambition.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 analyze 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 summarize and synthesize 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 outputsRequirements## 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 environmentsA team like no other.The Cadillac Formula 1 Team challenges conventions and redefines success through bold ambition, cutting-edge innovation, and an unwavering commitment to precision and excellence—on and off the track. This includes offering industry-leading pension, generous time off and, as part of a global brand, huge potential for career development.**Please note**Successful candidates must either be a U.S. Person (defined by U.S. law as U.S. citizen, U.S. permanent resident, asylee, or refugee) or a non-U.S. Person who is eligible to obtain any required export control authorization.As an equal opportunities employer, we are committed to the equal treatment of all current and prospective employees and does not condone discrimination on the basis of age, disability, sex, sexual orientation, pregnancy or maternity, race or ethnicity, religion or belief, gender identity or marriage and civil partnership. We aspire to have a diverse and inclusive workplace and strongly encourage suitably qualified applicants from a wide range of backgrounds to apply.At The Cadillac Formula 1 Team, all Team Members are expected to actively support and uphold our policies and procedures, including those focused on Environmental responsibility, Sustainability initiatives, Inclusion and Health and Safety practices.Please note that additional security checks may be required as part of the recruitment process. This may include a background check covering a minimum of the past five years and a criminal record check.