Paul is a seasoned AI engineer and strategic consultant with 8 years of experience in the field. He specializes in helping organizations leverage artificial intelligence to drive innovation. With extensive experience in GenAI, strategy consulting and cloud-based solutions, he has guided projects across multiple industries and company scales. Paul has led numerous initiatives ranging from Computer Vision research to scaling machine learning applications for enterprise use. His project portfolio includes developing voice assistants, complex agentic systems, autonomous drones, and predictive maintenance systems. Previously, Paul served as the CEO and Head of AI at Tensora GmbH, further refining his strategic consulting skills. By combining deep technical expertise with business acumen, he enables organizations to effectively implement AI strategies and achieve transformative results.
Collaborating with the CPO of an international freelancer platform to design and implement AI solutions that streamline and accelerate recruitment processes.
Collaborating with the CTO of a major U.S. corporation to develop AI prototypes and applications for various subsidiaries, focusing on rapid prototyping and tailored AI solutions for diverse business needs.
Developed a comprehensive suite of AI tools for the recruitment industry, including intelligent talent matching, automated screening, and LLM-powered candidate evaluation systems.
Developed an AI solution for accurate crowd counting in high-density settings for clients in professional sports and music festival industries, with cloud-based deployment and real-time analytics.
Built an automated GPT agent with multi-source data access (databases and web) to solve complex customer financial queries through intelligent information synthesis.
Developed a cognitive search engine leveraging OpenAI GPT, combining vector stores and keyword search to provide intelligent answers about internal company documents.
Created a Computer Vision framework and service enabling automated visual quality control on manufacturing shop floors with real-time defect detection.
Developed a global, AI-Act-compliant MLOps platform using AzureML and Databricks for scalable ML model deployment and governance.
Built an intelligent chatbot using OpenAI API that automatically transcribes interviews and generates comprehensive candidate evaluation reports.
Created a no-code data exploration and data cleaning platform that accelerates the work of Data Analysts and Data Scientists
Designed and built a modern machine learning architecture for an offering of different AI services in the Azure cloud.
Analyzed large amounts of customer data, built dashboards and predicted customer value & customer churn over time.
Data Science lead in a team of 4 to build a prototype web app that predicts potential flight delay and customer impact.
Built an AI recommender system that bridges the gap between supply and demand in the food industry.
Project lead for building an early warning system for manufacturing machines based on time-series models
Built a Time-Series-Forecast platform that retrains different models on a regular basis and serves the best model at scale.
Project lead of 3 for a COVID-19 computer vision solution to count people in public places and measure their distance
Built the Computer Vision part of an autonomous drone that detects and classifies damages in high resolutions images.