Hello! 👋

I'm Lily Shiomitsu

Fourth-year Computer Science Student at Northeastern University

About Me

I'm a fourth-year student studying Computer Science with a concentration in Artificial Intelligence and a minor in Spanish at Northeastern University. I have previously worked at Wolters Kluwer, UKG, and Coverys. These opportunities have allowed me to develop a strong foundation in DevOps, full-stack development, and frontend engineering. I'm passionate about building solutions that combine technical rigor with practical impact, and I thrive in collaborative environments where I can both contribute and continue learning. In my free time, I enjoy playing the piano and cello, traveling, and walking my dogs. I am currently seeking full-time opportunities for the summer of 2026, and I am excited for what lies ahead!

Java Python Groovy C++ QML JavaScript TypeScript HTML/CSS SQL

Education

Bachelor of Science in Computer Science

Northeastern University

Sep 2022 - May 2026
  • GPA: 3.92/4.0
  • University Honors Program, Dean's List all semesters
  • Concentration in Artificial Intelligence, minor in Spanish
  • Relevant Coursework: Algorithms and Data, Machine Learning and Data Mining 1, Fundamentals of Software Engineering, Computer Systems, Object-Oriented Design
  • Dialogue of Civilizations: Software Development and Innovation in Sydney, Australia 🇦🇺 (Summer 2025)

Experience

DevOps Software Engineer Co-op

Wolters Kluwer

Jan 2025 - Jun 2025
  • Built PR merge checks with smoke tests, Helm/YAML validation, and automated PR feedback, reducing configuration errors and improving deployment reliability
  • Parallelized smoke tests and automated service refreshes across 20+ web apps, saving 15 mins per release and hundreds of dev hours annually
  • Implemented zero-downtime deployments for test and mirror environments, saving 100-200 hours/year per 10 team members
  • Refactored scripts, added targeted seed job parameters, and upgraded JDKs, cutting build/seed times and improving maintainability

Software Engineering Intern

UKG

May 2024 - Aug 2024
  • Developed and optimized backend solutions in Java to address critical software defects and implement new features and updates for UKG’s Pro WFM software, enhancing system reliability and functionality
  • Resolved customer defects by deploying user applications with Kubernetes and debugging using hot swapping, improving the user experience and system performance
  • Conducted pseudo-locale testing to verify the localization readiness, identifying and addressing issues pre-release

AI Developer

Dropbox / Break Through Tech AI @ MIT

Aug 2024 - Dec 2024
  • Earned a Machine Learning Certificate from Cornell University through the Break Through Tech AI program at MIT
  • Built an NLP model in Python using OpenAI's GPT-3 to extract entities from booking emails and generate trip itineraries
  • Developed an end-to-end data pipeline in Streamlit integrating front-end and back-end components

Information Technology Co-op

Coverys

Jan 2024 - May 2024
  • Created engaging articles, videos, and courses for software updates using SharePoint, Camtasia, Snagit, and Audiate
  • Facilitated seamless onboarding sessions for new hires, delivering hands-on instructions to key applications
  • Collaborated with a team to redesign the main SharePoint site, enhancing user experience and simplifying navigation

Teaching Assistant

Northeastern University

Sep 2023 - Present
  • Fall 2025: DS 4400 (Machine Learning and Data Mining 1)
  • Fall 2024: CS 3000 (Algorithms and Data)
  • Fall 2023: CS 1800 (Discrete Structures)
  • Hold 5 hours of office hours per week to meet individual students for academic support and tutoring
  • Assist in weekly recitations, helping an average of 30 students per session with academic suppport
  • Grade assignments and exams, and answer students' questions on course material on Piazza

Projects

01

Speech-to-Text Web Application

A web application that compares transcripts from multiple speech-to-text providers against an original script, providing accuracy, latency, and word-error-rate metrics to help evaluate and select the most reliable speech-to-text system, with options to upload files, record directly, and download results. Developed in collaboration with the University of Sydney to support healthcare workers in dementia care. Code available upon request.

PythonFastAPIAmazon TranscribeDeepgramOpenAIGoogle CloudAssemblyAIGitHub