Internship - Computational Geometry Group

Join Our Team

We are the Audi Revolut F1® Team.

Audi will compete in the FIA Formula 1 World Championship starting in 2026.

The team has three locations. Audi's Motorsport Competence Center in Neuburg, Germany, is considered one of the most modern of its kind in Europe.

The Formula 1 Factory of Audi Motorsport AG in Hinwil (Switzerland) is known for its innovative technologies and passion for racing.

The Audi Motorsport Technology Centre in the UK, is in its launch phase and growing continuously. Our power unit comes from Neuburg, while Hinwil is responsible for chassis development and race operations.

What you need? The mindset of an athlete. If you are someone for whom giving up isn’t an option and limits are just something to be overcome, you can bring Vorsprung durch Technik to Formula 1 with us. Become part of this unique project and make motorsport history..

This position for the Audi Revolut F1® Team is based at Audi Motorsport AG in Hinwil, Switzerland.

Warum solltest du zu uns kommen?

• Practical, hands-on experience in a professional Motorsport environment 
• Mentorship and support from experienced colleagues 
• Exposure to real life F1 projects and business challenges 
• Development of key employability skills 
• Networking opportunities across the business

Training & Development

• Structured onboarding programme 
• Ongoing learning sessions / workshops 
• Access to internal training resources 
• Regular feedback and performance check-ins

Deine Aufgabe

This is an exciting opportunity for a motivated student to gain hands-on experience in Computational Geometry. You’ll work alongside experienced professionals and contribute to real projects that make an impact.
 

• Supporting day-to-day activities within the Computational Geometry group including prototype computational geometry algorithms and ship working code the team can build on 
• Assisting on building and experimenting with LLM-powered agents to automate geometric workflows across the F1 team 
• Prototype and experiment with computational geometry algorithms (meshing, spatial data structures, geometric reasoning, surface processing, etc.) applied to F1 car design and aerodynamics workflows 
• Collaborate with the team on research-driven projects and ship real, usable code that gets used by aerodynamicists, designers, and simulation engineers 
• Conducting research, analysis, or data entry as required 
• Research relevant papers and techniques, turning promising ideas into prototypes 
• Collaborating with team members, joining discussions, reviews and attending technical meetings 
• Presenting findings, demos, and progress clearly through documentation and write-ups
• Learn fast and pick up new tools, languages, and domains as the work demands 

Dein Profil

• Currently studying towards a degree in Mechanical Engineering, Computer Science, Aerospace Engineering or similar
• Strong interest in programming - you can write clean code and understand the fundamentals of software development, ideally in C#, C++ or Python
• Good communication and teamwork skills 
• Eagerness to learn and take initiative 
• Hands-on experience with LLMs and agents - you've built something with them; tool use, function calling, multi-step reasoning, RAG, agent frameworks - any of these. 
• Basic knowledge or familiarity with geometry, linear algebra, graphics, CAD, CFD, simulation, or motorsport engineering
• You have a builder's mindset - you finish things, you debug stubborn bugs, and you ship
• Ability to manage time and meet deadlines 

Bewerbe dich jetzt

Eligibility Criteria 

• Right to work in Switzerland (EU/EFTA citizenship or Swiss work permit)
• Available for the full 12 months of the programme 
• Available to start on 01.09.2026
• Internship as part of your study programme
• Studying a degree in Mechanical Engineering, Computer Science, Aerospace Engineering or similar

 
Application Process 
Interviews will take place in June & July with final outcomes expected by the end of July.
Due to the high volume of applications, we’re unable to provide individual feedback.