Elkanouni Othmane
About Elkanouni Othmane
Elkanouni Othmane is a Machine Learning Engineer with expertise in optimizing data processing and developing MLOps infrastructure. He has a strong academic background with degrees in Data Science, Engineering, and Mathematics, and currently works at Multiverse Computing in Spain.
Work at Multiverse Computing
Elkanouni Othmane currently serves as a Machine Learning Engineer at Multiverse Computing, a position he has held since 2023. His role involves the application of machine learning techniques to enhance data processing and model efficiency. Othmane's contributions include optimizing data workflows and implementing advanced algorithms to support the company's objectives in the field of machine learning.
Education and Expertise
Othmane has a solid educational background in engineering and data science. He earned a Master of Engineering (MEng) in Data Science and Engineering from Institut National des Postes et Télécommunications, completing his studies from 2018 to 2021. He also holds a Master's degree in Apprentissage, Vision et Robotique from Universite de Lorraine, which he completed in 2023. His studies in Mathematics and Physics at Classe préparatoire Mohammed V provided him with a strong foundation in analytical skills.
Background in Research and Development
Before joining Multiverse Computing, Othmane worked as a Research Assistant at Oracle in Switzerland for six months in 2021. This role allowed him to gain valuable experience in research and development within the tech industry. His work focused on leveraging machine learning and data processing techniques, which laid the groundwork for his subsequent achievements in the field.
Achievements in Machine Learning
Othmane has made significant contributions to machine learning applications, particularly in optimizing data processing and model performance. He successfully optimized data processing on AWS, achieving a 25% reduction in processing time. His development of a MLOps infrastructure led to a 30% decrease in model retraining time and an 8% reduction in cloud costs. Additionally, he implemented machine learning algorithms that improved wind energy forecasting accuracy for Acciona, reducing forecasting errors by 7.78%.
Technical Skills and Tools
Othmane possesses expertise in various AWS tools essential for data pipeline development. His skills include using Amazon S3, AWS Glue, AWS EC2, and AWS RDS. He has demonstrated his ability to achieve a 52% compression ratio for Large Language Models while maintaining 89% precision in critical tasks such as translation, showcasing his proficiency in machine learning and data optimization.