Intern AI Research – Defect identification and Root Cause Analysis

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Job ID: MER0003XTP At Mercedes-Benz Cars Development, we shape the mobility of the future. By this we mean innovative products of the highest quality as well as efficient development methods and processes.In the center MB.OS High Computing ECUs we develop the Zone Controllers with which we put Mercedes-Benz in the driver's seat for software development and software integration. For this we develop innovative technical solutions with new working methods. For our highly motivated development team we are looking for you as an Intern in our team. The ZC SWC integration is the key player in creating the final flash-ready ECU SW for the Zone Controllers in the Mercedes-Benz Operating System (MB.OS). The integration includes the continuous of the communication matrices, the integration of more than 50 software applications and the further development of the classic AUTOSAR stacks. During the application integrations, we have many validation errors which we analyze and write Solving Actions to for each of those errors. To make this process more efficient, we would like to utilize ML approach. We are seeking a motivated and detail-oriented Intern with AI background to do: Model Research: Conduct research on possible AI models for our use case

Data Preparation: Assist in curating and preparing datasets of from our database of known errors

Model Training: Training and fine-tuning the AI agent, ensuring it learns how to detect errors and suggest fixes

Testing & Validation: Test the AI agent's performance on different types of error code, validating the quality of error detection and the relevance of suggested fixes

Error Analysis: Analyze failed attempts and provide feedback to improve the AI agent's accuracy in and understanding fixing code issues

Documentation: Help document the training processes, including strategies for data preparation, error detection, and model performance improvements

The activity can begin from April 2026.

Currently pursuing a degree in Computer Science, Software Engineering, Data Science, or a related field

Experience with machine learning frameworks and developing AI agents is preferred (but may not be mandatory if the candidate demonstrates a strong willingness to learn and has a solid foundation in the field of Machine learning and Generative AI)

Experience with data annotation or similar tasks in AI training

Basic understanding or experience with Autosar is a plus

Strong analytical and problem-solving skills along with effective communication and collaboration skills

What You'll Gain: Hands-on experience in training an AI system that will shape the future of software development for Automotive ECUs

Exposure to cutting-edge AI techniques in natural language processing and machine learning

Opportunity to cooperate with industry professionals who thrive on tackling complex challenges

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. HR Services 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).

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