Summary
AI research and systems engineer with 6+ years of experience in multimodal pre-training and post-training, data curation, evaluation, open-source model integration, and production deployment. Built PyTorch training/serving systems and made 40+ contributions across the Hugging Face ecosystem, including 28 public pull requests authored in Transformers.
Resume downloads
- Machine Learning Engineer Resume - Clean Version (PDF)
- Software Engineer Resume - Long Version (PDF)
- Clean LaTeX source / Long LaTeX source
Open source
- Hugging Face ecosystem contributor with 40+ contributions, including 28 public pull requests authored in Transformers across model architectures, processors, conversion scripts, distributed training fixes, tests, and documentation.
- Hugging Face Transformers contributor: led the addition of Segment Anything 2 (SAM2) support to
huggingface/transformers.- Implemented and refined image/video segmentation model support, processors, documentation, conversion flow, and integration tests through a long-running community review cycle.
- PR: Add Segment Anything 2 (SAM2); merged 2025-08-13.
- Documentation: SAM2 model docs, credited as a model contributor.
- Hugging Face Transformers contributor: opened Add Molmo2 and published danelcsb/Molmo2-4B on the Hugging Face Hub.
Education
- M.S. in Electrical Engineering and Entrepreneurship, Korea Advanced Institute of Science and Technology, KAIST, 2020.03-2021.02
- B.S. in Electrical Engineering, Pohang University of Science and Technology, POSTECH, 2015.03-2020.02
- B.S. in Electrical and Computer Engineering, University of Illinois, Urbana and Champaign, UIUC, 2018.01-2018.12
Work experience
- 2026/01-Present: Data Scientist
- Toss Bank (토스뱅크)
- Building an on-premise agent system with internally deployed LLMs for secure AI-assisted development workflows.
- Developing AI-based authentication systems for face and ID card verification.
- Post-trained and evaluated an approximately 1B-parameter vision-language model in an end-to-end document extraction pipeline, reaching 61% exact-match accuracy for automation-ready outputs.
- 2021/09-2026/01: Machine Learning Engineer
- SuperbAI
- Held approximately one year of team-leadership responsibility, leading two ML engineers through multimodal pre-training and staged text/image alignment for a visual-grounding model using a curated 1.1M-image dataset.
- Built distributed, multi-GPU training and serving infrastructure with AWS Batch, TensorRT, and Triton Inference Server, improving inference throughput by 5x over pure PyTorch serving.
- Built LoRA, Adapter, and LST post-training pipelines and delivered 1,100+ models and 60+ customer endpoints in one year.
- Built interactive segmentation tools using RepViT-SAM, FocalClick, SAM, and SAM2, increasing segmentation labeling speed by 25x.
- Reduced GPU memory usage by 65.6% and training time by 44.3% using parameter- and memory-efficient training methods.
- Won 2nd place in IOD and 4th place in FSOD challenges at CVPR 2025.
- 2021/02-2021/08: Machine Learning Engineer Intern
- Kakao Enterprise
- Fixed AutoGluon NeuralNetFastAI scaling issue.
- Developed a Flask-based training and inference AutoML framework with a simple front-end.
- 2019/02-2020/06: Co. Team Island CTO
- Team Island
- Built ZZAZZ (째즈), a mobile video-editing application that applied customizable motion effects to people using detection/segmentation, 3D mapping, and tracking.
- Built lightweight CNN models for mobile applications and on-device inference.
- 2018/08-12: Undergraduate Researcher
- UIUC Undergraduate Research Program
- Improved direction-of-arrival estimation with the MUSIC algorithm using irregular microphone arrays.
- Generated binaural sounds through a software-based audio pipeline.
- Supervisor: Professor Romit Roy Choudhury
- 2018/06-08: Machine Learning Engineer
- Seerslab Intern
- Developed face landmark detection using Haar cascades, HOG features, and machine learning methods.
- Built a GUI tool for annotating face coordinates.
- Developed CMS login functionality with JWT-based authentication.
- 2017/03-06: Undergraduate Researcher
- POSTECH Undergraduate Research Program
- Developed a non-invasive heart-rate measurement device.
- Collaborated on a smart-watch FPGA module for a national research project.
- Supervisor: Professor Park Sung Min
- 2016/06-08: Research Intern
- ASAN Medical Center
- Designed simulations for an electrical surgical unit using electromagnetic field analysis tools.
- Supported development and experiments for an assistive device for knee-injured patients.
- Supervisor: Professor Choi Jae Soon
Skills
- Research: PyTorch, Hugging Face Transformers, multimodal pre-training and post-training, LoRA, contrastive alignment, evaluation
- AI systems: AWS Batch, distributed multi-GPU training, TensorRT, Triton Inference Server, MLflow, model conversion
- Programming: Python, Kotlin, Git; large open-source codebase development, testing, and documentation
- Deployment: mobile ML, lightweight CNNs, on-device inference, TensorFlow Lite
- AI developer tools: Claude Code, Codex, opencode, LangChain, Langfuse
- Hardware and tools: FPGA development with Xilinx, PyQt5
- Languages: Korean (native), English (professional)
Publications
Terahertz Signal Analysis in Tissue of Gastroesophageal Reflux Disease
Choi Sang Bum. (2013). &Terahertz Signal Analysis in Tissue of Gastroesophageal Reflux Disease." OPTICAL SOCIETY OF KOREA. POSTER SESSION I(WP-VI3).
On Joint Transfer of Energy and Information: A Markov Decision Problem Formulation
Sangbum Choi. (2018). "On Joint Transfer of Energy and Information: A Markov Decision Problem Formulation."None.
Improved DOA estimation of MUSIC algorithm based on irregular microphone array
Sangbum Choi. (2018). "Improved DOA estimation of MUSIC algorithm based on irregular microphone array." None. .
MobileHumanPose: Toward Real-Time 3D Human Pose Estimation in Mobile Devices
Sangbum Choi, Seokeon Choi, and Changick Kim. (2021). "MobileHumanPose: Toward Real-Time 3D Human Pose Estimation in Mobile Devices." IEEE/CVF CVPR Workshops, 2328-2338.
ZERO: Multi-modal Prompt-based Visual Grounding
Sangbum Choi and Kyeongryeol Go. (2025). "ZERO: Multi-modal Prompt-based Visual Grounding." arXiv.
Talks
Teaching
Athlete Service and Leadership
- Approximately one year of team leadership at SuperbAI, including leading two ML engineers on multimodal pre-training.
- Co-founder and CTO, Team ISLAND, 2019/02-2020/06.
- Led up to eight people simultaneously across leadership roles.
- Open-source contributor to Hugging Face Transformers