Arbeite als Intern- Scenario-based Virtual Verification-Automated Driving (m/f/d) bei CARIAD SE in München – Dein neuer Job wartet

At CARIAD, we're bundling and further expanding the Volkswagen Group's software expertise. We’re uniting over 6,500 global experts to build a scalable technology stack, including a software platform, unified electronic architecture and reliable connection to the automotive cloud. Our CARIDIANS are developing vehicle functions such as driver assistance systems, a next-generation infotainment platform, power electronics and charging technology, and digital services in and around the vehicle.

Our software can already be found in Volkswagen ID. models and will soon power Audi and Porsche vehicles with the E3 1.2 platform in 2024.

It's no easy task, but with experts like you, we can shape the future of mobility. Join us at CARIAD and be part of this exciting journey!

YOUR TEAM

We are a team of ambitious and highly motivated experts in the field of ADAS/AD innovation, searching for new solutions to cope with the current challenges in autonomous driving to create an empowering driving experince. Our current focus is to further develop compenents and features to promote assisated and automated driving. One of the challenges we are currently tackling is to come up with new algorithms to enable self-driving vehicles.

We are looking for an intern with a hands-on mentality to come up with innovative ideas and solutions on developing artificial algorithms for vehicle mass data, various situations and use cases. You get the chance to work with people across diverse teams, brands and background. Sounds exciting? We are thrilled to hear from you.

WHAT YOU WILL DO

• Support one of our PhD students in the field of data-driven virtual verification and driving scenario generation.
• Extract and analyze complex driving scenarios and develop feature representations from extensive real-world data.
• Analyze driving scenarios within large sets of data in order to enhance the understanding of diverse driving conditions.
• Derive results from state-of-the-art research on unsupervised learning and deep learning on driving scenario extraction/scenario generation.
• Integrate your implementations strategically into our simulation toolchain to enhance our virtual verification methods.

WHO YOU ARE

NICE TO KNOW

• Duration: 6 months
• 35-hour week
• Remote work options
• If you have further questions about the candidate journey at CARIAD, please contact us: careers@cariad.technology

YOUR RECRUITING CONTACT

Carmen Dörwald

At CARIAD, we value individuality and diversity. We see great strength in our differences and can all benefit from the unique perspectives of others. We strive to employ people with diverse backgrounds who have the expertise, energy and focus to advance our mission. If you're unable to submit an application because of a disability, please contact us at careers@cariad.technology.