Thesis: Internal Tool Development

The SWEET department at Koenigsegg is looking for motivated students interested in developing and evaluating internal tools within AI, data analysis, and vehicle diagnostics. We currently have several different thesis opportunities available, allowing students to choose a project based on their interests and background. The available thesis projects focus on exploring how AI and data-driven tools can support engineering and vehicle development at Koenigsegg. Depending on the selected project, the work may involve software and tool development, AI-agent implementation, data analysis, testing, and evaluation. The current thesis opportunities include: Tooling for Agent-Based Analysis of Large Time Series Data: Develop tools that enable AI agents to process and analyse large vehicle datasets, with the aim of making data analysis more efficient and accessible. Diagnostic Agent in Justera – Effectiveness and Measurable Value: Evaluate how an AI-based diagnostic agent can support vehicle troubleshooting and quantify its impact on diagnostic time, workload, and quality. Responsibilities Develop tools for AI agents to process and analyse large vehicle time-series datasets. Develop and evaluate AI agents for vehicle diagnostics and troubleshooting. Integrate AI agents with relevant tools and data sources. Evaluate AI performance using measurable criteria, such as diagnostic accuracy, time savings, and workload reduction. Write, test, and maintain reliable, high-quality software. Document findings and collaborate with engineers and other stakeholders to identify improvements. Requirements Pursuing a B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related field. Programming experience in C++ and familiarity with scripting languages such as Python. Familiarity with software development practices, including version control, testing, and code reviews. Understanding of common software design principles and a strong focus on code quality, maintainability, and performance. Interest in AI agents and their applications in data analysis and vehicle diagnostics. Willingness to learn new technologies and a proactive, problem-solving mindset. Strong teamwork and communication skills, with the ability to explain technical concepts clearly to non-technical stakeholders. Professional proficiency in English. Good to have Experience developing applications using large language models (LLMs), AI agents, or tool calling. Familiarity with the Model Context Protocol (MCP), including developing or integrating MCP servers to connect AI agents with tools and data sources. Experience processing and analysing time series data or evaluating AI systems against measurable performance criteria. Availability According to agreement In your cover letter, please describe: Why you would like to do your Thesis in this department? What you hope to learn and achieve during your time here? What experience or background you already have within this area? #LI-DNI