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Schedule Interview NowMy name is Carlos B. and I have over 0 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, ETL, Data Analysis, Natural Language Processing, Text Analytics, etc.. I hold a degree in Bachelor's degree. Some of the notable projects I've worked on include: Winner – Arabic Lexical Disambiguation, NeurIPS 2023 LLM Efficiency Challenge – Winning Model, AI-Powered Financial Analysis System, Legal Guidance AI Assistant. I am based in Encarnacion, Paraguay. I've successfully completed 4 projects while developing at Softaims.
I am a dedicated innovator who constantly explores and integrates emerging technologies to give projects a competitive edge. I possess a forward-thinking mindset, always evaluating new tools and methodologies to optimize development workflows and enhance application capabilities. Staying ahead of the curve is my default setting.
At Softaims, I apply this innovative spirit to solve legacy system challenges and build greenfield solutions that define new industry standards. My commitment is to deliver cutting-edge solutions that are both reliable and groundbreaking.
My professional drive is fueled by a desire to automate, optimize, and create highly efficient processes. I thrive in dynamic environments where my ability to quickly master and deploy new skills directly impacts project delivery and client satisfaction.
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Logicalis Paraguay S.A
Achieved 1st place in Word Sense Disambiguation (WSD) and 2nd place in Location Mention Disambiguation (LMD) at the ArabicNLP shared task, ACL 2024. Designed advanced models using Llama 3 and Cohere,
Contributed to the winning solution at the NeurIPS 2023 LLM Efficiency Challenge, organized by Meta AI and Microsoft Research. Developed Birbal, a Mistral-7B-based model fine-tuned on a single GPU (RT
Built an AI-driven financial analysis system leveraging RAG and LLMs to process stock data, financial news, SEC filings, and PDF documents. The platform generates source-linked reports, manages long a
Developed a Legal Assistant application using Retrieval-Augmented Generation (RAG) to deliver affordable, reliable, and context-aware legal guidance under Saudi Arabian law. The system allows users to
Bachelor's degree in Computer science
2015-01-01-2020-01-01