Raquel Pérez Arnal
About Raquel Pérez Arnal
Raquel Pérez Arnal is a Machine Learning Engineer with a strong analytical mindset and a background in high-performance artificial intelligence. She has transitioned from research roles to engineering and has experience in academia as an associate professor.
Work at sennder
Raquel Pérez Arnal has been employed at sennder as a Machine Learning Engineer since 2022. In this role, she applies her expertise in machine learning to develop solutions that enhance operational efficiency. Her position is based in Barcelona, Cataluña, España, and follows a hybrid work model. This transition to sennder marks a significant step in her career, allowing her to leverage her analytical skills and experience in a dynamic environment.
Previous Experience at Barcelona Supercomputing Center
Raquel Pérez Arnal worked at the Barcelona Supercomputing Center from 2018 to 2023. Initially, she served as a Research Student in High Performance Artificial Intelligence for two years, where she gained foundational experience in the field. Following this role, she advanced to a Research Engineer position, contributing to various projects focused on high-performance computing and artificial intelligence for three years. This experience solidified her analytical mindset and technical skills.
Academic Background
Raquel Pérez Arnal studied at Universitat Politècnica de Catalunya, where she earned a Grado en Matemáticas from 2012 to 2018. She furthered her education by obtaining a Master in Artificial Intelligence from the same institution, completing her studies in 2019. This academic foundation provided her with a strong grounding in mathematics and artificial intelligence, which she applies in her professional roles.
Teaching Experience
Raquel Pérez Arnal has held teaching positions at Universitat Politècnica de Catalunya. She served as an Associate Professor for the Machine Learning subject in both Bachelor and Master programs. Her tenure as an Associate Professor for the Bachelor program lasted four months in 2020, while her role for the Master program extended from 2021 to 2023. These positions allowed her to share her knowledge and expertise with students in the field of machine learning.
Analytical Skills and Programming Preferences
Raquel Pérez Arnal demonstrates a keen interest in uncovering insights from data, indicative of her strong analytical mindset. She prefers using structured programming patterns for data analysis rather than relying solely on notebooks. This preference reflects her commitment to developing robust and maintainable code, which is essential in the field of machine learning engineering.