Software Engineer Intern · AMD
Austin, TX
Returning Summer 2026.
Jae Park
Studying Computer Science + Statistics at the University of Illinois at Urbana-Champaign with expected graduation May 2027.
Focused on backend and full-stack development with interests in applied ML/AI.
Currently a part-time Software Engineer at printpal.io, building software in the 3D printing industry.
Returning Software Engineer Intern at AMD and previously an AI Engineer Intern at FANUC America.
Experience
Summer 2026
May 2025 — Aug 2025
Software Engineer Intern · AMD
Austin, TX
I built a CPU trace system for EPYC server processors with three components: a Rust decoder that parsed raw trace data into signals for post-silicon debug analysis; a full-stack visualization platform (FastAPI, React, SQL, S3) for uploading and collaboratively sharing trace files; and a Python tracing library that abstracted trace complexity and enabled automated tracing of EPYC processors.
May 2023 — Present
Software Engineer · printpal.io
Chicago, IL
Working on a social marketplace platform for 100,000+ 3D printing users in Flask, JavaScript, SQL (printpal.io). Implemented features including infinite scrolling with Redis caching, distributed task processing with Celery, and Elasticsearch-powered search for users and models. Built a Swift mobile app connected to backend AI models that allows users to generate and preview AI 3D models from text and images. Shipped an admin dashboard with real-time analytics visualizations.
Sep 2025 — Dec 2025
Software Engineer · Disruption Lab
Champaign, IL
Worked on an AI-driven customer discovery platform to help founders validate pain points through simulated multi-turn interviews. Implemented a conversation pipeline with the OpenAI API for natural discovery flows and structured qualitative feedback. Developed a responsive React/Next.js frontend for managing interview sessions, state, and real-time responses.
May 2024 — Aug 2024
AI Engineer Intern · FANUC America
Hoffman Estates, IL
Led the development of an on-premises RAG chatbot using LangChain and C# that allowed engineers to query CNC documentation conversationally. Developed and tested a PDF chunking strategy in C# that optimized retrieval quality from CNC documentation. Built a test framework and benchmarks using real production queries to accurately measure and optimize model performance. Researched emerging LLM techniques to create a roadmap for future development.
Projects
A full-stack machine learning system that predicts NBA game outcomes
AI project that turns course syllabus PDFs into structured deadlines and syncs them to Google Calendar.
BoomerAI
Desktop assistant that walks non–tech-savvy users through real websites.
Computer vision project to detect and prevent hands touching your face for acne.