AI/ML • Software • Systems

Jaeyoung Lee (Daniel)

SDE at AWS • Stanford CS (MS/BS)

I build scalable software and ML systems—from cloud infrastructure to LLM-powered products.

Portrait of Jaeyoung Lee

Highlights

The intersection I enjoy most: systems × ML × product.

Scalable Systems

Cloud services, data pipelines, dashboards, and reliability-focused engineering.

Applied ML

LLMs, NLP/CV, and practical ML workflows from prototypes to shipped features.

Fast Iteration

Automation, tooling, and UX details that make complex systems feel effortless.

Skills

A quick snapshot of the tools I use most.

Languages

Python C++ JavaScript SQL

ML & AI

PyTorch TensorFlow NumPy Pandas LLMs NLP CV

Tech

AWS Linux FPGA VHDL Unreal Engine Git

Education

Stanford CS (AI) — MS & BS.

Stanford University

MS, Computer Science (AI) 2024–2025 (Graduated)

Stanford University

BS, Computer Science (AI) 2021–2025 (Graduated)
  • Tau Beta Pi
  • Stanford Astronomical Society (President)
  • Stanford ACM

Experience

Recent roles across software engineering and applied ML.

Software Development Engineer

Amazon Web Services (AWS)
08/2025–Present
  • Network Management Team.
  • Building scalable systems for AWS network infrastructure.

SDE Intern — Network Capacity

Amazon Web Services
06/2024–09/2024
  • Migrated capacity planning stack to AWS cloud, cutting cost & enabling rapid iteration.
  • Shipped a dashboard serving faster updates & custom views for users/orgs.

ML Intern

SLAC National Accelerator Lab
09/2023–05/2024
  • Automated ML-to-FPGA (VHDL) model conversion for high-throughput inferencing.
  • Accelerated hardware deployment, reducing prototyping time.

ML Intern, AI Graphics Lab

NCSOFT, Korea
06/2023–08/2023
  • Developed an audio-to-facial animation ML pipeline for Unreal Engine assets.
  • Sped up character facial animation by 7× via model/Py pipeline.

Software Eng Intern

SLAC National Accelerator Lab
06/2022–08/2022
  • Built realtime GUI for high-speed image + statistics for X-ray lab scientists.
  • Optimized UX for large-scale visual/scientific data.

Projects

Selected projects across LLMs, automation, and graphics.

MBenz Meeting Prep Assistant

01/2024–06/2024
  • Real-time, voice-based AI summaries for scheduling as you drive.
  • Integrates calendar, LinkedIn, and Wikipedia for sharp, on-the-road prep.
LLMs Voice API

Auto Email → Calendar Sync

02/2024–03/2024
  • LLM-powered event parsing → calendar automation; no manual copy-paste.
LLMs Automation Python API

Knowledge Navigator w/ LLM

09/2023–12/2023
  • Smart doc search GUI with LLM answers + source links; 4× faster retrieval.
LLMs Retrieval GUI Python

ML Ray-Traced Images

04/2023–06/2023
  • GAN renders high-fidelity ray-traced frames from raster images; 4.5× faster than classic.
ML GANs Graphics PyTorch/TensorFlow

Audio → Face Model Optimization

09/2022–12/2022
  • Redesigned net → 60% faster training, no loss of quality.
ML Audio Animation

Contact

Let’s connect about ideas, collaboration, or opportunities — email or LinkedIn preferred.