Xenia Skotti is an AI research engineer and Member of Technical Staff with 11 years of experience applying NLP and generative models to real-world problems, currently based in Oregon. She has driven production LLM summarization and proactive credit risk monitoring at JPMorgan Chase, co-authoring an EMNLP 2024 paper and boosting statement-level factual accuracy by 20%. Comfortable across research and engineering, she builds end-to-end solutions from evaluation rigs and backtesting packages to matching algorithms that link GPT outputs to source documents. A committed community builder, she co-leads the Glasgow Ignite AI/ML group to grow peer learning and technical communication. Her open-source contributions include backend improvements to the prominent Solidus e-commerce framework, reflecting a strong Ruby/Rails and systems mindset alongside AWS and Elasticsearch experience. Colleagues describe her as a continuous learner who translates cutting-edge models into dependable, auditable systems for high-stakes domains.
10 years of coding experience
3 years of employment as a software developer
MSci Computing Science, Computer Science, MSci Computing Science, Computer Science at University of Glasgow
🛒 Solidus, the open-source eCommerce framework for industry trailblazers.
Role in this project:
Back-end Developer
Contributions:6 commits, 21 PRs, 104 comments in 2 years 10 months
Contributions summary:Xenia contributed to the back-end logic of the Solidus e-commerce framework. Their work included fixing a bug related to the ordering of payments, enhancing the flexibility of report generation, and refactoring payment method handling. Additionally, the user improved the API by dynamically loading payment source views and adding documentation for required partials. These modifications demonstrate a focus on improving both the functionality and maintainability of the Solidus codebase.
Contributions:2 releases, 6 PRs, 6 pushes in 3 years 7 months
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Xenia Skotti - Member Of Technical Staff at Tomoro