Intern Autonomous Driving

Mercedes-Benz AG

Mercedes-Benz Plant Sindelfingen, Sindelfingen (Hybrid)

Job Type Full-time

Posted 1 week 1 day ago

Hybrid

In our department for Autonomous Driving Research and Development, we are committed to shaping the future of mobility through the development of highly automated driving systems for highway and urban environments. Our work covers the research, development and validation of advanced machine learning methods, perception systems and decision-making algorithms for next-generation autonomous vehicles.

We are looking for an Intern Autonomous Driving (Mandatory Internship) to support our research activities in uncertainty estimation for end-to-end autonomous driving.

Tasks

Conducting a comprehensive literature review of state-of-the-art end-to-end autonomous driving approaches and uncertainty estimation methods
Evaluating and selecting suitable uncertainty estimation techniques for integration into end-to-end autonomous driving systems
Integrating and validating uncertainty estimation methods within the end-to-end driving pipeline
Analyzing the impact of uncertainty on planning and decision-making, particularly in novel and rare driving scenarios
Implementing, optimizing and evaluating machine learning frameworks for training and validation purposes

What you can expect

Insights into cutting-edge research and development in autonomous driving
Collaboration with experienced experts in machine learning and automated driving technologies
Opportunities to contribute to innovative research projects with real-world relevance
Access to state-of-the-art development and evaluation environments
An international and interdisciplinary working environment

The activity can begin from November 2026.

Qualifications

Studies in Computer Science, Robotics, Physics, Mathematics, Electrical Engineering or a comparable course
Strong programming proficiency in Python
Solid understanding of deep learning methods, particularly neural networks, as well as experience with software frameworks such as PyTorch and the MMDetection family
Hands-on experience with Linux and software development in Linux environments
Very good communication skills and proficiency in English
Ability to work in a team
Analytical way of thinking and strategic way of working
Engagement

Preferred qualifications

Knowledge of perception, prediction, planning and uncertainty estimation
Experience publishing research results at deep learning or robotics conferences, including collaborative publications
Hands-on experience with containerization technologies such as Docker
Familiarity with Large Language Models, Vision Language Models and Vision-Language-Action Models

Additional information

Applications should include a resume, cover letter, certificates, current certificate of enrollment stating the semester, proof of mandatory internship if applicable, and proof of the standard period of study. Documents should be marked as relevant for the application in the online form and must not exceed 5 MB.

Severely disabled applicants and applicants with equivalent status are welcome. Support is available from the representative for severely disabled employees at sbv-sindelfingen@mercedes-benz.com.

For questions about the application process, contact People Solutions at myhrservice@mercedes-benz.com or 0711/17-99000.