Chanwoo Kim
Engineering Manager at Hyundai Motor Company (현대자동차)
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolChanwoo Kim is an Engineering Manager at Hyundai Motor Company in Seoul with eight years of experience bridging automotive quality engineering and machine learning. He specializes in high-end Genesis vehicle programs while continuously contributing to ML open-source projects—most notably adding constrained beam search and an M-CTC-T model to the widely used Hugging Face transformers library. His hands-on background includes designing new loss functions and tests for pytorch-metric-learning, reflecting strong applied research-to-product skills. Trained in mechanical engineering at Chung-Ang University, he brings a systems-level view that combines vehicle engineering rigor with practical ML engineering. Colleagues rely on him to translate complex algorithmic ideas into tested, production-ready components.
9 years of coding experience
Baccalauréat, 기계공학부, Baccalauréat, 기계공학부 at 중앙대학교
English, Korean
Github Skills (15)
transformers10
metric-learning10
pytorch10
machine-learning10
nlp10
language-model10
deep-learning10
python10
natural-language-processing10
testing9
speech-recognition9
computer-vision9
flax4
tensorflow4
jax4
Programming languages (6)
Github contributions (5)
KevinMusgrave/pytorch-metric-learning
Oct 2021 - May 2022
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Role in this project:
ML Engineer
ML EngineerContributions:4 reviews, 19 commits, 13 PRs in 6 months
Contributions summary:Chanwoo primarily contributed to the implementation and testing of a new loss function, `CentroidTripletLoss`, within the `pytorch-metric-learning` framework. Their work included defining the loss function, writing the test code to validate this loss function, which involved debugging the code for return types. Additionally, the user implemented the `VICRegLoss`.
metric-learningpytorchdeep-learningcomputer-visionmachine-learning
huggingface/transformers
Feb 2022 - Jun 2022
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Role in this project:ML Engineer
ML EngineerContributions:26 reviews, 5 commits, 10 PRs in 3 months
Contributions summary:Chanwoo primarily contributed to the implementation of constrained beam search functionality within the transformers library, a key aspect of natural language processing. They developed and refined classes for constrained beam search, including the `ConstrainedBeamSearchScorer` and `DisjunctiveConstraint` classes. They also addressed bug fixes, documentation, and test integration, ensuring the functionality integrated correctly with the existing codebase. The user's contributions included implementing the M-CTC-T model, including the feature extractor, processor, tokenizer and its tests.
audioinferencemachine-learning-modelsmultimodaltransformers
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