Working Student / Internship / Thesis - End-to-end Automated Driving with World Models (m / w/d) | Students

YOUR TEAM

• We offer you an exciting opportunity for your master thesis, for an internship or a working student job in our AI Core team in the field of end-to-end AI for automated driving. End-to-end networks enable joint optimization of the driving stack, allowing training of different tasks (such as perception and planning) in one model. The aim of this master thesis / the internship is to assess and enhance end-to-end machine learning models for automated driving. Your focus will be optimizing network architectures for efficient single-stage training and closed-loop evaluation, while achieving compatibility with predictive world models.

• 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.

NICE TO KNOW

• Remote work options within Germany

• Internship/Thesis:

• Duration: 3 - 6 months

• 35 hours/week

• Salary: 13,90 €/hour

• Working Student

• Duration: 6 months (with the option to extend up to two years)

• 20 hours/week, up to 35 hours/week during the semester break

• Salary: 17,80€/hour

Company

• CARIAD SE

Contract

• Fixed-term

Department

• Apprenticeship & Study

Shift

• Full-time

Experience

• Students

Wymagania

• Very good academic performance

• Master student in Computer Science, Robotics, Electrical Engineering or similar

• 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 and 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

Zakres obowiązków

• Research and assess open-source end-to-end neural networks for automated driving

• Employ pretrained foundational models to leverage their representational power within the end-to-end network

• Improve networks for single-stage training and optimize for closed-loop performance

• Adapt the end-to-end model to be compatible with a predictive world model

• Conduct extensive experiments on public and internal datasets

• Work closely with our machine learning experts and PhD students with the aim for a scientific contribution

Opis

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! 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.