Internship / Master Thesis – Latent Predictive World Models for End-2-End Autonomous Driving (f/m/d)

Job title: Internship / Master Thesis – Latent Predictive World Models for End-2-End Autonomous Driving (f/m/d)

Company: Volkswagen


Job description: 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 TEAMWe offer you an exciting opportunity for your master thesis or for an internship in our ADAS/AD Pre-Development team in in the field of model engineering for autonomous driving. For the following topic you get the responsibility: latent predictive world models. The aim of this master thesis / the internship is to assess the current research on latent world models, to evaluate how they can be employed and to integrate a pre-trained model in our AD/ADAS stack and/or learning environment. The department works on software and machine learning models for automated driving in urban environments. Within this department, we are a team of ambitious and highly motivated experts in the field of self-driving vehicles working in an agile environment to advance the autonomous driving stack.WHAT YOU WILL DO

• Research and assess the state-of-the-art of latent world models for autonomous driving
• Finetune existing world models on automotive datasets for latent state forecasting
• Conduct extensive experiments on public and internal datasets
• Assess the usage of world models for end-2-end motion planning and closed-loop training
• Work closely with our PhD students and the model engineering team

WHO YOU ARE

• Enrolled Master student in the area of Computer Science, Robotics, Electrical Engineering or similar
• Very good academic performance
• Good general knowledge in the field of (self-)supervised learning, transformer-based architectures, and (vision) foundation models
• Very good knowledge of machine learning frameworks such as PyTorch
• Applied knowledge in software development and programming in Python and C++
• Structured and independent work, above-average commitment and flexibility
• Strong communication skills and analytical understanding

NICE TO KNOW

• Remote work options within Germany
• Duration: 6 months with the option to extend
• 35-hour week

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 – we are happy to support you.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 TEAMWe offer you an exciting opportunity for your master thesis or for an internship in our ADAS/AD Pre-Development team in in the field of model engineering for autonomous driving. For the following topic you get the responsibility: latent predictive world models. The aim of this master thesis / the internship is to assess the current research on latent world models, to evaluate how they can be employed and to integrate a pre-trained model in our AD/ADAS stack and/or learning environment. The department works on software and machine learning models for automated driving in urban environments. Within this department, we are a team of ambitious and highly motivated experts in the field of self-driving vehicles working in an agile environment to advance the autonomous driving stack.WHAT YOU WILL DO

• Research and assess the state-of-the-art of latent world models for autonomous driving
• Finetune existing world models on automotive datasets for latent state forecasting
• Conduct extensive experiments on public and internal datasets
• Assess the usage of world models for end-2-end motion planning and closed-loop training
• Work closely with our PhD students and the model engineering team

WHO YOU ARE

• Enrolled Master student in the area of Computer Science, Robotics, Electrical Engineering or similar
• Very good academic performance
• Good general knowledge in the field of (self-)supervised learning, transformer-based architectures, and (vision) foundation models
• Very good knowledge of machine learning frameworks such as PyTorch
• Applied knowledge in software development and programming in Python and C++
• Structured and independent work, above-average commitment and flexibility
• Strong communication skills and analytical understanding

NICE TO KNOW

• Remote work options within Germany
• Duration: 6 months with the option to extend
• 35-hour week

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 – we are happy to support you.Job ID: 16613Company: CARIAD SELocation:München, DE, 80807 Ingolstadt, DE, 85053Department: Apprenticeship & StudyCareer Level: StudentsWorking Model: Full-timeContract Type: Fixed-termRemote Working: By agreementPosting Date: Aug 1, 2025Why CARIAD?We believe that how we work together is just as important as the technology we create. We strive to take action with a can-do attitude, and value speed over perfection. We aim to collaborate with mutual trust, taking accountability for our actions. We foster transparency and welcome diverse perspectives as we learn, adapt, and grow togetherMore informationHR contactDo you have any suggestions or questions? ✉️Legal Notices

Expected salary:

Location: München, Bayern

Job date: Sun, 03 Aug 2025 06:21:36 GMT

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