kyle ton

|student, software engineer

hello, i'm . . .

kyle ton, a sophomore at orange coast college studying computer science! i am an aspiring software engineer with a passion for creating and developing full-stack applications, with some cloud computing and machine learning integration.

i have a large interest in machine learning and ai, particularly in language models natural language processing and be able to work on integrating machine learning with software development, or even directly contribute to the advancement of the field itself! i am getting started with machine learning models right now, teaching myself the basics of machine learning and ai, and i hope to apply this towards cool projects in the future!

my goal for my career one day is to become a full-stack software engineer! perhaps one day, i will try to transition into machine learning and ai engineer roles and contribute to the advancement of the artificial intelligence sector! please feel free to contact me for anything at all!

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canon sd700is - japan 04.2024

about me

family and friends
i love hanging with family and friends, and exploring new places. ive started playing pickleball and have been playing throughout college. lmk if youre down to hit sometime!
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education

bachelor's in mathematics and computer science

university of california, san diego - la jolla, ca

aug 2025 - jun 2027

possibly minoring in data science or artificial intelligence

transfers' in computer science

orange coast college - costa mesa, ca

jun 2023 - aug 2025

relevant coursework: object oriented programming, computer architecture and assembly, discrete mathematics, data structures and algorithms, linear algebra, single and multivariable calculus, differential equations.

high school diploma

la quinta high school - westminster, ca

sep 2019 - jun 2023

gpa: 3.93/4.35 | rank: 36/550

awarded seal of biliteracy in spanish.

experience

ai engineering intern

product manager accelerator - remote

oct 2024 - dec 2024

developed a full-stack application to enhance resumes, using an llm pipeline to analyze and increase industry-specific keywords and relevance.

also implemented a mongodb database to store and manage resumes, storing over 100 resumes and allowing for efficient retrieval and analysis.

software engineering intern

trace - garden grove, ca

aug 2024 - oct 2024

created automated scripts for camera testing, for version control and calibration, increasing efficiency and accuracy of quality assurance and documentation.

using baud rates of camera modules, i diagnosed issues in the pre-release module software updates, leading to a more efficient and reliable update-integration process.

ai trainer - language models

dataannotation - remote [part-time]

jun 2024 - dec 2024

evaluated and improved the accuracy of language model responses in various subjects, including various programming languages, validating performance and consistency.

ai software engineering fellow

headstarter ai - remote

jul 2024 - sep 2024

worked in a group setting, creating full-stack applications with generative ai applications, learning and using various apis and technologies.

also participated in a hackathon, creating a natural language processing application, parsing and analyzing data from a csv file and classifying it based on sentiment, entering it into a postgresql database.

projects

matchpointai

python, react, tailwind css, scikit-learn, seaborn, pandas, numpy, jupyter notebook

may 2025 - present

project is still under construction

a full stack machine learning application that uses xgboost to predict the likelihood of a tennis match outcome

feature engineered custom player stats using historical tennis match data

inspired by me playing tennis and wanting to know whether prime federer would beat alcaraz and/or sinner

git-lint

python, fastapi, github webhooks, openai api (gpt-4o-mini + text-embedding-3-small), pinecone db, docker, aws lambda + s3

may 2025

a little play on eslint, but for github code diffs + syntax review + security vulnerability analysis

an automated fastapi service that reviews github pull requests and analyzes the code for security vulnerabilities, performance issues, and code quality, using gpt-4o-mini

also auto-updates embeddings with changes from the diffs

implemented rag with pinecone db and openai text-embedding-3-small to provide context to model for better code reviews, with codebase embedding hashes stored in s3 for validation

stocksense

next.js, spring boot, postgresql, tailwind css, shadcn, google oauth2.0, aws s3, docker, redis, vercel, railway.app

feb 2025 - apr 2025

note: deployment is down -> railway.app free trial credits expired. i am working on getting the deployment back up soon

a full stack application that displays stock information and stock data visualization. it gathers information based on user input and displays stock numerical data and a chart visualization. using sentiment analysis, it gathers recent related news and articles and analyzes them for a positive/negative rating.

the idea came from me trying to get a more holistic understanding of the market to try and keep my roth ira a net positive (unsuccessful so far)

skills

languages: html/css, javascript, python, java, c++, sql

frameworks: rest api, react, express, fastapi, next.js, flask, spring boot

tools/applications: git, firebase, mongodb, postgresql, aws, vercel, docker, redis, postman, visual studio

machine learning: numpy, pandas, matplotlib, seaborn, scikit-learn

socials  [@kylehton]

my github contributions

 

thank you for visiting my website! it was made completely from scratch using tailwindcss, next.js, shadcn, magic ui, and framer motion.