I am a Generative Artificial Intelligence Engineer and AI researcher based, currently working at EPAM NEORIS and pursuing a Ph.D. in Artificial Intelligence at the Universidad Politécnica de Madrid. My background combines strong academic research with real-world industry experience, allowing me to design AI solutions that are both cutting-edge and production-ready. I have worked extensively on Natural Language Processing, computer vision, and audio/sound analysis, developing advanced models using PyTorch, TensorFlow, LangChain, and modern LLM ecosystems. In industry, I build RAG systems and intelligent agents integrated with vector databases and external services, focusing on scalable, contextual, and efficient AI applications. In research, I have designed novel transformer-based architectures that outperform state-of-the-art methods while significantly reducing computational cost. What sets me apart is my ability to bridge research and engineering. I have published multiple peer-reviewed papers in high-impact journals and conferences.This means I don’t just prototype ideas, I turn them into robust, efficient systems. Previously, I worked as an AI Researcher at a National Technology Centre, where I led projects in sound classification, contrastive learning, reinforcement learning, and computer vision. My academic foundation includes a Master’s degree in Machine Learning and Big Data and a Bachelor’s degree in Computer Engineering with honors in AI-related subjects. Overall, I help clients transform complex AI challenges into practical, high-performance solutions backed by solid research and real-world experience.…I am a Generative Artificial Intelligence Engineer and AI researcher based, currently working at EPAM NEORIS and pursuing a Ph.D. in Artificial Intelligence at the Universidad Politécnica de Madrid. My background combines strong academic research with real-world industry experience, allowing me to design AI solutions that are both cutting-edge and production-ready. I have worked extensively on Natural Language Processing, computer vision, and audio/sound analysis, developing advanced models using PyTorch, TensorFlow, LangChain, and modern LLM ecosystems. In industry, I build RAG systems and intelligent agents integrated with vector databases and external services, focusing on scalable, contextual, and efficient AI applications. In research, I have designed novel transformer-based architectures that outperform state-of-the-art methods while significantly reducing computational cost. What sets me apart is my ability to bridge research and engineering. I have published multiple peer-reviewed papers in high-impact journals and conferences.This means I don’t just prototype ideas, I turn them into robust, efficient systems. Previously, I worked as an AI Researcher at a National Technology Centre, where I led projects in sound classification, contrastive learning, reinforcement learning, and computer vision. My academic foundation includes a Master’s degree in Machine Learning and Big Data and a Bachelor’s degree in Computer Engineering with honors in AI-related subjects. Overall, I help clients transform complex AI challenges into practical, high-performance solutions backed by solid research and real-world experience.WWWW…