David Biertimpel
About David Biertimpel
David Biertimpel is a Software Engineer at TomTom in Berlin, Germany, with a background in computer vision, machine learning, and psychology.
Current Role at TomTom
David Biertimpel is currently employed as a Software Engineer at TomTom. He has been with the company since 2021 and is based in Berlin, Germany. His role involves working on various software engineering projects, potentially leveraging his expertise in computer vision and machine learning.
Previous Work Experience
Before his current role, David accumulated diverse experience in multiple roles. He worked as a Computer Vision Engineer at Figment in 2021 for 7 months. Prior to that, he served as a Machine Learning Research Intern focusing on Autonomous Driving at TomTom in 2020 for 10 months in Amsterdam. His early career included roles such as Research Intern at the Spinoza Centre for Neuroimaging in 2019, Research Assistant at the University of Hamburg in 2017-2018, and Student Employee at BurdaForward in 2015.
Educational Background
David holds a Master of Science in Artificial Intelligence from the University of Amsterdam, completing his degree in 2020. He also earned a Bachelor of Science in Human Computer Interaction from the University of Hamburg, where he studied from 2014 to 2018. His academic background provides a strong foundation in both theoretical machine learning and practical applications of these technologies.
Research and Internship Experience
David's research experience includes an internship at the Spinoza Centre for Neuroimaging in 2019 and a research assistant role at the University of Hamburg in 2017-2018. Additionally, he worked as a Machine Learning Research Intern at TomTom, focusing on Autonomous Driving in 2020. This diverse research background contributes to his expertise in AI and computer vision.
Passion for Computer Vision and Machine Learning
David has a strong interest in computer vision research and its practical applications. He is passionate about creating inductive biases to reflect the structure of problems, leading to data-efficient solutions. His skills in theoretical machine learning, combined with his software development background and knowledge in psychology, make him a versatile professional in the tech industry.