Yassir Benkhedda
About Yassir Benkhedda
Yassir Benkhedda is a Data Scientist and Machine Learning Engineer with extensive experience in developing machine learning systems across various fields. He has worked for notable companies such as Apple and currently holds a position at Unit8 SA in Switzerland.
Work at Unit8
Yassir Benkhedda has been employed at Unit8 SA as a Data Scientist and Machine Learning Engineer since 2019. In this role, he focuses on the development and deployment of machine learning systems. His responsibilities encompass the entire lifecycle of machine learning projects, including model prototyping, production deployment, and MLOps tooling. His work contributes to various initiatives within the company, enhancing Unit8's capabilities in data science and machine learning.
Previous Experience
Before joining Unit8, Yassir Benkhedda held several positions that contributed to his expertise in data science and machine learning. He worked at Apple as a Machine Learning Engineer for six months in 2019 in the Zürich Area, Switzerland. Prior to that, he was an Engineering Intern at nViso for three months in 2016 and completed a Master Thesis Project at Axis Communications from 2015 to 2016. Additionally, he served as a Research Assistant at Idiap Research Institute for 11 months in 2017.
Education and Expertise
Yassir Benkhedda holds a Bachelor of Science (BSc) in Electrical Engineering, Electronics, and Communications from EPFL (École polytechnique fédérale de Lausanne), which he completed from 2010 to 2014. He further advanced his education by obtaining a Master of Science (MSc) in Information Technologies from EPFL from 2014 to 2016. His academic background provides a strong foundation for his work in machine learning, particularly in areas such as computer vision, natural language processing, causal inference, and generative modeling.
Contributions to the Field
Yassir Benkhedda has actively participated in various conferences and initiatives related to artificial intelligence and machine learning. He contributed to the Applied Machine Learning Days conference, focusing on AI applications in manufacturing. Additionally, he was involved in creating a practical guide on Large Language Models, which highlights advancements in AI. He also participated in a Unit8 Talks session that discussed machine learning techniques with limited labeled data.