Internship / Masters Thesis - Inverse Reinforcement Learning for Vehicle Functions (m/f/d)

We are CARIAD, the automotive software company of the Volkswagen Group. Our teams build automotive software platforms and digital customer functions for iconic brands like Audi, Volkswagen, and Porsche – supporting the Volkswagen Group in becoming the leading automotive technology company. With CARIDIANS in Germany, the USA, China, Estonia, and India, we are transforming automotive mobility for everyone.

Join us and be part of this exciting journey!

YOUR TEAM

For the department Vehicle, Energy, Motion & Body (VEMB) we are looking for a student (intern or master thesis) for the project “Learning Intelligent Onboard Functions”. Our department develops advanced software for vehicle energy, motion, and body systems. Our VEMB pre-development team works on methods for end-to-end learning of VEMB functions to enable faster, scalable and more cost-effective product development. We cover the entire development range, from initial concepts to proof of concepts in test vehicles. Thereby, we work in close cooperation with the series development departments.

WHAT YOU WILL DO

• Collaborate closely with the PhD candidates to address the key challenges in Reinforcement Learning, with a focus on VEMB functions
• Review the state of the art in Inverse Reinforcement Learning
• Select, implement, and adapt a suitable IRL method to infer reward functions from expert demonstrations 
• Design and execute experiments (e.g., baselines, ablations, robustness checks) to evaluate performance and transferability
• Apply the learned reward models to downstream reinforcement learning tasks
• Document and communicate results. Publication of research results is desired
• Collaborate with teams in pre-development and series development 

WHO YOU ARE

• Enrolled student in the a relevant field: Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, etc.
• Solid background in control theory, Reinforcement Learning, or imitation learning
• Interest or prior experience in Inverse Reinforcement Learning, learning from demonstrations, or reward learning
• Experience in Python and with machine learning frameworks such as PyTorch, Jax, etc.
• Hands-on experience through real-world projects, such as student projects, internships, or prior work experience
• Strong analytical and problem-solving skills
• High level of commitment, initiative, and teamwork
• Fluency in English and German and good communication skills

NICE TO KNOW

• Remote work options within Germany 
• Duration: 6 months 
• 35-hour week 
• Salary: 13,90 €/hour 

At CARIAD, we embrace individuality and diversity because we believe our differences make us stronger. We actively seek to build teams with a variety of backgrounds, perspectives, and experiences. Our goal is to create an environment where everyone feels valued and empowered to contribute. If you need assistance with your application due to a disability, please reach out to us at careers@cariad.technology - we are happy to support you.