Kim Minkyu is a Machine Learning Engineer with nine years of experience building production ML systems, from ETL and recommender pipelines to NLP and personalized advertising at scale. Based in South Korea, he has driven end-to-end ML work at Toss Securities and NAVER, combining research-grade modeling with robust workflow and infra skills (Airflow/argo, Kubernetes, Docker, Hadoop ecosystem). He contributes to open-source ML tooling—evidenced by implementing and extending SpecAugment across TensorFlow and PyTorch—and focuses on practical, reproducible deployments. His background spans research (ETRI) to applied finance and e-commerce, giving him a strong sense for data quality, debiasing, and measurable model performance.
9 years of coding experience
10 years of employment as a software developer
Master of Science (MS), Computer Science, 3.79/4.3, Master of Science (MS), Computer Science, 3.79/4.3 at 서울대학교
Bachelor of Science (BS), computer science, 3.48/4.3, Bachelor of Science (BS), computer science, 3.48/4.3 at 한국과학기술원(KAIST)
A Implementation of SpecAugment with Tensorflow & Pytorch, introduced by Google Brain
Role in this project:
ML Engineer
Contributions:26 commits, 1 PR, 27 pushes in 7 months
Contributions summary:Kim primarily contributed to the implementation and improvement of SpecAugment, a data augmentation technique for speech processing. Their work involved modifying the `spec_augment.py` file by updating remarks, fixing typos, refactoring code, and integrating time warping using Tensorflow's `sparse_image_warp`. Furthermore, the user added a PyTorch version and test code for the SpecAugment algorithm. This indicates a focus on enhancing and expanding the functionality of the SpecAugment implementation across different frameworks.
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Kim Minkyu - Machine Learning Engineer at Toss Securities