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Schedule Interview NowMy name is Diego V. and I have over 1 year of experience in the tech industry. I specialize in the following technologies: Machine Learning, Data Analysis, Artificial Intelligence, Computer Vision, Natural Language Processing, etc.. I hold a degree in Master of Science (MS), Doctor of Philosophy (PhD), Bachelor of Applied Science (BASc). Some of the notable projects I've worked on include: Post-Editing with RAG and LLMs, Dynamic RAG System for CSS Selector Extraction in E-Commerce, EarthView, Logo Detection With No Priors, Pay Attention to the Activations, etc.. I am based in Barcelona, Spain. I've successfully completed 7 projects while developing at Softaims.
Information integrity and application security are my highest priorities in development. I implement robust validation, encryption, and authorization mechanisms to protect sensitive data and ensure compliance. I am experienced in identifying and mitigating common security vulnerabilities in both new and existing applications.
My work methodology involves rigorous testing—at the unit, integration, and security levels—to guarantee the stability and trustworthiness of the solutions I build. At Softaims, this dedication to security forms the basis for client trust and platform reliability.
I consistently monitor and improve system performance, utilizing metrics to drive optimization efforts. I'm motivated by the challenge of creating ultra-reliable systems that safeguard client assets and user data.
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Developed a cutting-edge Retrieval-Augmented Generation (RAG) mechanism to enhance the performance of Large Language Models (LLMs) for machine translation and post-editing tasks. The system efficientl
Designed and implemented a Retrieval-Augmented Generation (RAG) system leveraging LLMs to extract CSS selectors from any e-commerce website worldwide in any language. Integrated a live monitoring serv
Developed EarthView, a large-scale dataset for self-supervised learning on remote sensing data, featuring 15 tera pixels of imagery from sources like NEON, Sentinel, and Satellogic. Introduced EarthMA
Focused on enhancing Detection Transformer (DETR), an end-to-end object detection model that eliminates the need for domain-specific priors. Evaluated DETR's performance on logo detection and analyzed
Designed a modular attention mechanism for fine-grained image recognition, focusing on lower-level feature activations to enhance classification accuracy and robustness against deformation, pose varia
Master of Science (MS) in Computer Vision
2019-01-01-2020-01-01
Doctor of Philosophy (PhD) in Machine Learning
2020-01-01-2023-01-01
Bachelor of Applied Science (BASc) in Computer science
2015-01-01-2019-01-01