Javier Esteve Meliá
About Javier Esteve Meliá
Javier Esteve Meliá is a Machine Learning Engineer with a strong background in electronics and automation. He has experience in developing machine learning models, particularly in object detection and natural language processing, and has worked for several companies in the field of artificial intelligence.
Work at LanguageWire
Javier Esteve Meliá currently holds the position of Machine Learning Engineer at LanguageWire, a role he has been in since 2023. In this capacity, he focuses on developing and implementing machine learning models, leveraging his expertise in artificial intelligence to enhance the company's offerings. His work involves applying advanced techniques in natural language processing and deep learning.
Education and Expertise
Javier Esteve Meliá has a solid educational background in engineering and artificial intelligence. He studied at Universitat Politècnica de València (UPV), earning a degree in Engineering in Electronics and Automation from 2010 to 2014. He furthered his education by attending Pi School, where he received a School of Artificial Intelligence Scholarship in 2019 for 11 months. In 2022, he completed a course on Natural Language Processing with Transformers at Sphere.
Background
Javier Esteve Meliá has a diverse professional background in machine learning and data science. He began his career at Capgemini, where he worked as a Machine Learning Engineer from 2016 to 2020. He then joined Solver IA in 2020 for 11 months, followed by a position at SDG Group as a Machine Learning Engineer from 2020 to 2021. He transitioned to Zinklar as a Senior Data Scientist from 2022 to 2023 and later worked at Uniphore in a similar role from 2021 to 2022.
Achievements in Machine Learning
Throughout his career, Javier Esteve Meliá has developed machine learning models specializing in object detection and semantic segmentation. He has also been involved in testing advanced deep learning techniques, particularly in the field of natural language processing. His experience includes working on time series analysis projects using deep learning methodologies.