An experienced professional in information processing technologies, specializing in Natural Language Processing (NLP), Machine Learning (ML), and Information Retrieval (IR). With over 8 years in the field, roles have included data scientist in R&D projects, AI-focused initiatives, and as a lecturer and PhD candidate in Business Intelligence and Information Retrieval with an emphasis on NLP. Proficient in utilizing Deep Learning Language Models (LM/LLM), developing indexing techniques, and conducting information system searches through crawling and searching methodologies, in addition to expertise in distributed data processing and analysis.

Career involvement has encompassed large-scale projects handling massive datasets and developing machine learning algorithms for extracting meaningful insights. Experiences include implementing supervised and unsupervised machine learning models for a variety of applications such as text classification, summarization, and the fine-tuning of large language models for specialized problem-solving.

Possesses extensive knowledge in distributed system architectures and parallel processing, with a particular focus on the Apache Spark ecosystem. Proficiency includes working within environments that demand high efficiency and scalability, contributing to the optimization of data processing pipelines (ETL) and the deployment of resilient big data solutions.