Introduction

In my career as a technical writer, my work centered around language, whether that was documenting SDKs, managing multilingual content, or polishing translated text. I can make highly technical information clear, usable, and accessible to diverse audiences. I bring this decade of experience in documentation and localization project management to my work in human language technology.

Before pivoting fully into tech, I worked in roles that combined administrative and technical responsibilities, especially within the mental health and non-profit sectors. While my titles were often administrative, my day-to-day work involved auditing documentation, creating how-tos, and writing user-facing content that supported both compliance and usability. These experiences sharpened my attention to detail and laid the foundation for my transition into more technically focused roles.

After moving to Sweden, I kickstarted my international career with a technical writing role at an iGaming studio. I collaborated closely with translators, engineers, and game designers, but most often with QA testers. Together, we managed large-scale localization workflows to ensure content was not just accurate, but also culturally relevant and user-friendly.

That experience solidified my love for content strategy and led me to complete a bachelor’s degree in Technical Communication from Arizona State University. Through this program, I deepened my understanding of global content strategy and the operational side of multilingual product development. My work reinforced the importance of linguistic diversity and accessibility, and it pushed me to think more critically about how people interact with technology across languages and regions.

The idea to explore natural language processing was born from a casual watercooler chat with those QA testers. They were venting about how soul-crushing it was to manually comb through 15 of the same assets in 29 different languages. I couldn’t stop thinking about how inefficient that sounded, and how easily one small oversight could snowball into a release-blocking nightmare. I recalled an incident where one small mistranslation took an entire day of production to fix.

That watercooler chat lit a fire: what exactly would help automate this process? Something that could flag outdated strings, detect industry-specific mistranslations, or even highlight missing content across versions. I wanted to find out. That curiosity led me to do some heavy research and pursue graduate study in NLP, where I could learn to build the tools that support QA teams and streamline multilingual workflows.

As of today, I have completed a Master of Science in Human Language Technology at the University of Arizona. While my initial interest in the field was driven by the practical challenge of automating localization testing, my time in the program has broadened my understanding of the scope of the field’s wider impact. Through the program, I’ve come to appreciate not just the complexity of human language, but the enormous potential NLP has to support linguistic inclusion, accessibility, and representation in technology. Now, I’m looking for opportunities to build or refine NLP tools that make multilingual products more accessible, automate tedious QA processes, and help real teams ship better content, faster.