Niels Rogge

Niels Rogge

Machine Learning Engineer @ ML6

About Niels Rogge

Niels Rogge is a Machine Learning Engineer currently working at ML6 in Belgium since 2023. He has a background in Business and Information Systems Engineering and experience in retrieval-augmented generation using large language models.

Work at ML6

Niels Rogge has been employed as a Machine Learning Engineer at ML6 since 2023. The company, based in Belgium, specializes in artificial intelligence solutions. In this role, he applies his expertise in machine learning to develop innovative AI applications. His work involves collaboration with teams to enhance AI capabilities and deliver impactful solutions to clients.

Education and Expertise

Niels Rogge holds a Master's degree in Business and Information Systems Engineering from KU Leuven, which he completed from 2017 to 2019. He also earned a Bachelor's Degree in the same field from 2014 to 2017. Additionally, he studied Innovation et Entrepreneuriat Social at IÉSEG School of Management in 2015. His educational background equips him with a strong foundation in both technical and business aspects of machine learning.

Background in Applied AI Research

Prior to his current role at ML6, Niels Rogge worked as an Applied AI Researcher at HOWEST University of Applied Sciences from 2020 to 2021. In this position, he focused on advancing AI research initiatives. His experience in academia contributed to his knowledge of machine learning applications and methodologies.

Experience with Machine Learning Technologies

Niels Rogge has significant experience in machine learning technologies, particularly in retrieval-augmented generation (RAG) using large language models. He is proficient in implementing AI solutions using tools such as PyTorch and Google Colab. His projects often involve natural language processing and computer vision, showcasing his versatility in the field.

Contributions to Open Source Projects

Niels Rogge actively contributes to open-source libraries, including HuggingFace Transformers. His contributions focus on state-of-the-art deep learning models, reflecting his commitment to advancing the field of machine learning. This involvement allows him to collaborate with other developers and researchers in the AI community.

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