Dohyun Kim is a Machine Learning Engineer with 14 years of software experience, currently improving recommendation and multimodal search systems at Bucketplace using Python, TensorFlow, PyTorch, Go, Spark, and Airflow. He has a strong applied ML background from Samsung Research, where he built object-detection models for robotics (vacuum cleaners), and a track record of shipping production media and streaming features at NAVER and LINE. Dohyun blends research-minded modeling (metric learning, multimodal architectures) with pragmatic systems work—optimizing pipelines, inference, and data workflows for real products. His open-source contributions include Bluetooth stack fixes to Samsung’s widely used TizenFX, reflecting low-level systems fluency beyond typical ML roles. A Hanyang University software engineering graduate with a 3.8 GPA, he is comfortable spanning from device APIs to scalable ML services and improving reliability at every layer.
14 years of coding experience
1 year of employment as a software developer
Bachelor, School of Computer Science, Major of Software Engineering, 3.8, Bachelor, School of Computer Science, Major of Software Engineering, 3.8 at Hanyang University
Contributions:47 reviews, 32 commits, 30 PRs in 4 years
Contributions summary:Dohyun's contributions primarily focused on fixing and improving Bluetooth functionalities within the TizenFX framework. Their work involved addressing GATT (Generic Attribute Profile) issues, adding parameters to event arguments, and resolving BLE (Bluetooth Low Energy) adapter problems. The changes included modifications to BluetoothStructs, BluetoothLeAdapterImpl, and BluetoothGatt files, indicating a focus on Bluetooth API implementation and enhancement. These fixes likely improved the stability and reliability of Bluetooth connectivity in the Tizen environment.
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Dohyun Kim - Machine Learning Engineer at Bucketplace