Leipzig, Saxony, Germany
As Lead AI Engineer at levelbuild AG, I focus on revolutionizing IT consulting in the construction industry by developing tailored AI solutions integrated with a NoCode platform and hosted on Microsoft Azure. Working alongside my team, I lead multiple AI projects from ideation to deployment, delivering accessible web application tools to benefit thousands of users. Holding a Bachelor of Applied Science in Informatik (Game Engineering) from Hochschule für angewandte Wissenschaften Kempten, I am driven by a commitment to creating impactful, user-centric solutions. My core competencies include project management, cross-functional team leadership, and leveraging cutting-edge AI technologies to address complex challenges in innovative ways.
I lead the development of AI-supported digitalisation, automation, and intelligent assistance systems for ERP-adjacent platforms in the German construction industry. At levelbuild, I design and build practical AI solutions that improve document-heavy back-office processes, modernise operational workflows, and make large amounts of business information easier to search, understand, and act on. My work includes: Integrated AI assistant systems for construction-industry ERP environments OCR and document-processing pipelines for scanned PDFs, contracts, plans, invoices, and e-invoices Automated tagging, classification, summarisation, metadata extraction, and semantic analysis RAG-based chat and search systems across large document inventories and operational databases Multi-tenant, provider-agnostic architecture patterns with permission-aware data access Client-facing AI consulting, requirements structuring, architecture planning, and delivery ownership I work closely with clients and internal stakeholders to turn vague AI ideas into realistic, scalable systems that create measurable operational value. Several of my automation workflows have accelerated back-office and document-processing tasks by up to 60–80%. Beyond implementation, I contribute to technical direction, architectural validation, prioritisation, hiring, and cross-team planning, with a strong focus on building maintainable systems instead of isolated AI demos.
As an Independent Contractor for tracker.gg, I spearheaded the development of advanced features and machine learning solutions, enhancing the website's backend and user interface. My role focused on leveraging data science to tackle complex challenges, from data mining and feature engineering to model deployment and inference. Key accomplishments include: Valorant Player MMR Estimation: Designed and implemented a machine learning model to estimate Valorant players' hidden Match Making Rating (MMR) using recent match performances and ranks. The model, trained on datasets provided by Riot Games, significantly improved the accuracy of player rankings on tracker.gg. Fortnite Tournament Outcome Prediction: Developed a live service application that monitors Fortnite tournaments in real-time, predicting outcomes and advising players on strategies to maximize their chances of qualifying for prizes. This tool has become a cornerstone for providing actionable, live guidance to the gaming community. Performance Metrics Development: Conceptualized and implemented a suite of data-driven metrics to quantify player performance, utilizing historical data to offer a comprehensive analysis of player skills and strategies. In this role, I not only delivered data-driven solutions to enhance gaming analytics but also established a foundation for continuous innovation in the esports domain, directly impacting player engagement and website traffic growth.
At ALTEN, I embarked on my career as a Junior ML Engineer, where I specialized in the development and implementation of machine learning algorithms tailored for autonomous vehicle simulation. My role was characterized by a blend of technical innovation, research, and application in real-world scenarios. Key contributions include: Machine Learning Algorithm Development: Engineered and implemented sophisticated machine learning algorithms from the ground up in C++, designed to power the learning process of simulated autonomous vehicles within Unreal Engine 4 environments. This endeavor laid the groundwork for advanced simulations, enhancing the in-engine learning capabilities of virtual cars. Unreal Engine 4 Integration: Successfully integrated machine learning functionalities into Unreal Engine 4, enabling the realistic simulation of autonomous driving vehicles. This integration was pivotal in simulating complex driving scenarios and behaviors, significantly contributing to the development of intelligent, self-navigating systems. Research and Innovation: Led independent research initiatives to explore novel ideas and principles in machine learning and its applications to autonomous driving. This involved a proactive approach to understanding cutting-edge technologies and leveraging them to advance the project's goals. Industry Collaboration and Impact: Contributed to a research project aimed at exploring the potential of machine learning in developing real-world autonomous driving technologies. The project, funded due to ALTEN's connections with prominent automotive brands like BMW, highlighted the practical implications and potential of our research in shaping the future of autonomous vehicles. Throughout my tenure at ALTEN, I not only honed my technical skills in machine learning and software development but also contributed to pivotal research that bridges the gap between virtual simulations and real-world autonomous driving applications.
Werkstudent role in full-time. Managing large amounts of complex, unstructured content for the latest Red Bull website.