Intern Autonomous Driving

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Job ID: MER00048N9 In our department for Autonomous Driving Research and Development, we are involved in 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. For this exciting and challenging area, we are looking for an Intern Autonomous Driving (Mandatory Internship) to support our research uncertainty in estimation for end-to-end autonomous driving. These challenges await you: Conducting a comprehensive literature review of state-of-the-art end-to-end autonomous driving approaches and uncertainty estimation methods Evaluating and screening suitable uncertainty 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, especially 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.

Studies in the field of Computer Science, Robotics, Mathematics, Electrical Engineering or a comparable course Physics Strong programming proficiency in Python Solid understanding of deep learning methods, particularly neural networks, as well as experience with common 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 Commitment 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 search as Docker Familiarity with Large Language Models (LLMs), Vision Language Models (VLMs) and Vision Language Action Models (VLAMs) Additional information: We look forward to receiving your online application, including a resume, cover letter, certificates, current certificate of enrollment stating your semester, proof of mandatory internship if, and proof of the standard period of study. Please remember to mark your documents as ''relevant for this application' in the online form and observe the maximum file size of 5 MB. You can find further information on the hiring criteria here. Severely disabled applicants and applicants with equivalent status are welcome! The representative for severely disabled employees (sbv-sindelfingen@mercedes-benz.com) will gladly support you in the application process. People Solutions will be happy to help you with any questions you may have about the application process. You can reach us by email at myhrservice@mercedes-benz.com or by phone at 0711/17-99000 (Mon-Fri 10am-12pm & 1pm-3pm).

Meal discount Mobile Phone for Employees Possible Discounts for Employees Possible Annual Profit Share Possible Events for Employees Coaching Flextime possible Hybrid Work Possible Health Benefits Company Retirement Mobility Offers Parking Inhouse Doctor Good Public Transport Barrier-Free Workplace Near-Site Childcare Canteen, Café