Generative AI for Automotive Software Engineering

TU München

Ilmenau, Germany

7 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Job source

portal.mytum.de

Tech stack

Artificial Intelligence Automation of Tests Code Generation Computer Programming Continuous Integration Software Debugging DevOps Python (Programming Language) Software Architecture Software Engineering Verification and Validation (Software) Large Language Models

+5 more

Generative AI Hardware Infrastructure Automotive Software Devsecops Vulnerability Analysis

Job description

Research and development of LLM- and VLM-based methods for automotive software engineering
Development of agentic AI systems with Human-in-the-Loop mechanisms for software development, testing, deployment, and maintenance
Design and implementation of Retrieval-Augmented Generation (RAG) pipelines using automotive standards, technical documentation, software models, and source-code repositories
Development of AI-supported methods for code generation, code transformation, software updates, and platform-specific software adaptation
Automation of automotive DevOps and DevSecOps workflows, including continuous integration, testing, verification, security analysis, deployment, and monitoring
Development of generative AI methods for automated test-case generation, software validation, vulnerability analysis, and debugging
Integration of locally deployable LLMs and VLMs into privacy-sensitive industrial development environments
Evaluation of the developed approaches using automotive use cases, simulation environments, and software-defined vehicle platforms
Publication of research results at leading international conferences and in scientific journals
Collaboration with academic and industrial partners within a large interdisciplinary research project

Requirements

A completed master’s degree in Computer Science, Artificial Intelligence, Software Engineering, Robotics, or a related field
Strong experience in software development and excellent programming skills, preferably in Python
Knowledge of machine learning, Large Language Models (LLMs), Vision Language Models (VLMs), or generative AI
Experience with Retrieval-Augmented Generation (RAG), AI agents, model-driven engineering, DevOps, DevSecOps, or automated testing is advantageous
Interest in automotive software engineering, software-defined vehicles, and future mobility technologies
Strong analytical and scientific skills and motivation to pursue a doctorate
Ability to work independently and contribute effectively to an interdisciplinary and international research team
Excellent written and spoken English, We look forward to receiving your application. It should include a curriculum vitae, relevant certificates and transcripts, and a brief statement describing your previous experience, research interests, and motivation for pursuing a doctorate in generative AI and automotive software engineering.

Benefits & conditions

Flexible working hours with home office options
A friendly, international, and open working atmosphere with state-of-the-art research infrastructure
Access to modern computing and GPU infrastructure for the development and evaluation of LLM-, VLM-, and agentic AI solutions
Research across the entire automotive software development lifecycle, from requirements and software architecture to code generation, testing, deployment, and maintenance
Participation in a major national research project involving leading academic and industrial partners
The opportunity to contribute your own ideas, define research priorities, and shape the future of AI-supported automotive software engineering
Close collaboration with automotive manufacturers, suppliers, technology companies, and research institutions
Comprehensive scientific supervision and support for pursuing a doctorate
Opportunities to publish at high-ranking international conferences and in scientific journals
A full-time position with payment according to TV-L E13