Sofia Páramo is a software engineer at Microsoft with eight years of experience building full-stack and infrastructure solutions across cloud, telecom, and consumer platforms. A summa cum laude Computer Science graduate from Tecnológico de Monterrey, she combines strong TypeScript skills with Java, C++, Python, and practical experience in Kubernetes, certificates, and CI/CD. Her work spans production services at Oracle and Microsoft, performance-focused platform improvements at her university, and hands-on open-source contributions—most notably enhancing an auto-synced translated dubbing tool by improving TTS, Azure integration, and DeepL fallbacks. People-driven and community-minded, Sofia is a GitHub Campus Expert and Women Techmakers Ambassador who brings fast learning, curiosity, and a knack for simplifying complex workflows. Based in Seattle, she balances pragmatic engineering with a creative, daydreamer’s perspective that often surfaces elegant, user-focused improvements.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Computer Science and Technology, 97, Bachelor of Science - BS, Computer Science and Technology, 97 at Tecnológico de Monterrey
Physics and Mathematics, 98, Physics and Mathematics, 98 at Preparatoria Jefferson
Graphic Programming, C.S. Fundamentals, Graphic Programming, C.S. Fundamentals at ENES Morelia, UNAM
Automatically translates the text of a video based on a subtitle file, and then uses AI voice services to create a new dubbed & translated audio track where the speech is synced using the subtitle's timings.
Role in this project:
Back-end Developer
Contributions:4 reviews, 8 commits, 4 PRs in 5 days
Contributions summary:Sofia primarily focused on enhancing the functionality and robustness of the auto-synced translation dubbing project. Their contributions included fixing bugs related to the Text-to-Speech (TTS) and Azure Speech service integration, improving directory validation, and managing dependencies. Furthermore, they implemented DeepL translation capabilities, added fallback mechanisms, and introduced a setting for stopping the process at the translation phase for manual review. They also made improvements and corrected region-specific language codes.
Personal website and project showcase built using React
Contributions:3 reviews, 95 commits, 49 PRs in 11 months
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