PhD student Data & AI Driven Automotive SW Quality

Mercedes-Benz; Sindelfingen (Stadt); Hybrid; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading automotive company in Sindelfingen is seeking a highly motivated PhD student to enhance software quality through intelligent, data-driven methods. Candidates should have a Master's degree in Computer Science or related fields, with experience in AI, programming, and a passion for automotive software. This position offers various employee benefits and a hybrid work model.

Leistungen

Health measures

Employee discounts

Flexible working hours

Hybrid working

Employee events

Qualifikationen

• Passion for automotive software and quality.
• Experience with bug issue systems and agent technologies.
• Knowledge in data science or data analytics is helpful.

Aufgaben

• Explore and develop AI-based solutions to enhance software quality.
• Analyze and prioritize data sources for monitoring software.
• Propose new data collection strategies based on findings.

Kenntnisse

AI / ML background

Software engineering

Data science

Programming in C, C++, Python

Agile software development

Business fluent English

Ausbildung

Master Degree in Computer Science or related field

Tools

Software-versioning tools (Git)

Vehicle operating systems

Jobbeschreibung

Overview

In Mercedes-Benz Cars Research & Development (RD), we are shaping the future of the coming generations of Mercedes-Benz vehicles. We stand for the most innovative products of the highest quality and aspire to be leaders in the fields of electromobility and vehicle software. It is therefore our daily business to work on the technologies and vehicles of tomorrow.

Data, AI, and connected vehicles are at the forefront of our digital transformation with MB.OS at Mercedes-Benz. We are looking for a highly motivated and talented PhD student to join our team and help us redefine the way we collect and work with vehicle data.

Objective

Join our mission to revolutionize software quality assurance at Mercedes-Benz by leveraging cutting-edge AI techniques and our flexible vehicle data collection infrastructure. This PhD position focuses on enhancing software quality through intelligent data-driven and AI-based methods.

Vision

Imagine a system that continuously scans diverse sources—from internal bug tracking systems to public online forums—for software-related issues. It consolidates this information into a unified view of current problems and automatically triggers targeted data collection jobs to verify and quantify the reported issues. This proactive approach enables earlier detection of software quality issues and provides developers with a stronger, data-backed foundation for debugging and resolution.

Your Role

You will explore and develop AI-based solutions to continuously monitor and improve software quality across the vehicle lifecycle. Your work will span:

• Data Source Identification: Analyze and prioritize internal and external data sources such as development vehicles (CarLa, MB.OS Data Collection), production vehicles, test benches, defect tracking systems, public forums, and social media.
• Issue Analysis: Develop models to classify, consolidate and assess software issues (e.g., bug vs. feature, severity, frequency, root cause).
• Data Collection Strategy: Propose and validate new data collection strategies for software quality based on the findings.
• AI Application: Investigate where AI can be most effectively applied in the software quality pipeline and identify current limitations to its adoption.

Research Questions

• Where can AI deliver the most value in automotive software quality assurance?
• What are the current barriers to AI adoption in this domain?
• How can agent-based AI systems (Agent2Agent) be used to automate the software improvement loop?

Technologies & Methods

• Agentic AI (Agent2Agent architectures)
• Multimodal data integration (internal + external sources via MCP)
• Automated generation of MB.OS Data Collection jobs
• Natural language processing and anomaly detection

Promotion & Supervision

The promotion can begin from November 5. The requirement for hiring is the supervision of the PhD project by a university lecturer. The PhD student is responsible for choosing his / her / their own supervisor.

Qualifications

• Master Degree or similar in Computer Science, Information Technology, Electrical Engineering or a comparable qualification
• Background in AI / ML, software engineering, or data science
• Passion for automotive software and quality
• Experience with bug issue systems, LLMs and agent technologies
• Knowledge of vehicle operating systems (Linux, QNX, AUTOSAR classic and adaptive) and embedded software development
• Programming skills in C, C++, Python and use of software-versioning tools (i.e. Git)
• Experience in agile software development
• Knowledge in data science or data analytics is helpful
• Business fluent English skills
• Self-management abilities
• Excellent Communication and Teamwork

Additional information

Please apply exclusively online and mark your application documents as "relevant for this application" in the online form. Please find the criteria of employment. Citizens of countries outside the European Union please send, if applicable, your residence / work permit.

Please understand that we do not accept paper applications and that there is no right to have your documents returned.

Benefits

Essenszulagen, Mitarbeiterrabatte, Mitarbeitermobilität, Mitarbeiter-Events, Flexible Arbeitszeit, Hybrides Arbeiten, Gesundheitsmaßnahmen, Betriebliche Altersversorgung, Mobilitätsangebote

Consent & Note

We need your consent to load the YouTube service! We use a third party service to embed video content that may collect data about your activity. Please review the details and accept the service to watch this video.

This content is not permitted to load due to trackers that are not disclosed to the visitor. The website owner needs to setup the site with their CMP to add this content to the list of technologies used.