Eunik Park | ML Engineer

About Me

I am a 3-year experienced ML Engineer specializing in making AI models lightweight, fast, and efficient. My primary focus is on Efficient AI, particularly Quantization. I optimize various models (Vision, Audio, LLM) for mobile, GPU, and NPU platforms.

Skills

Work Experience

ML Engineer @ SqueezeBits

06/2022 - Present

• Optimizing models for target hardware & platforms
• Enhancing performance-speed trade-offs through PTQ and QAT
• Conducted benchmarking of vLLM and TensorRT-LLM serving

Internship @ LG CNS

07/2021 - 08/2021

• Built AWS 3-tier web service using Terraform

Projects

OwLite

08/2023 - Present

[Website] [Github] [OwLite Examples]

• Developed a framework for easy model quantization from PyTorch to TensorRT
• Implemented various quantization algorithms and simulations
• Produced various examples and identified optimization patterns

Fits-on-Chips

02/2024 - 06/2024

[Website]

• Conducted comprehensive performance benchmarking of LLM serving frameworks
• Implemented evaluation module
• Wrote blog post, [vLLM vs TensorRTLLM] weight-activation quantization

Efficient Keyword Spotting Research

02/2024 - 06/2024

• Presented poster at Interspeech 2024
  RepTor: Re-parameterizable Temporal Convolution for Keyword Spotting via Differentiable Kernel Search
• Developed CNN-based KWS model using structural reparameterization
• Implemented Latency-aware Neural Architecture Search
• Achieved 97.9% accuracy with 183μs latency on Galaxy S10 CPU

Education

POSTECH

• Bachelor's in IT Convergence Engineering
• 03/2016 - 09/2023

Changwon Science High School

• 03/2014 - 02/2016