성용 박

Key Skills

Software

CrowdSource

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

Image

3D Sensor

Document

Top Label Types

Segmentation

Cuboid

Classification

Freelancer Overview

I am a detail-oriented data specialist with extensive experience in high-precision data annotation for AI training, particularly in domains such as autonomous driving (LiDAR), infrastructure monitoring (crack detection), and academic classification. My background in architectural engineering enables me to handle complex numerical and coordinate-based data with exceptional accuracy, consistently maintaining error rates below 1% even on large-scale, repetitive projects. I excel at executing segmentation tasks, managing high-volume datasets, and optimizing workflows to improve project turnaround times. My analytical mindset and commitment to data integrity ensure that I deliver reliable, high-quality labeled datasets that drive successful machine learning and AI initiatives.

Labeling Experience

Data Annotation Specialist – 3D LiDAR Object Recognition

Internal Proprietary Tooling3D SensorCuboid

I executed high-precision 3D bounding box annotations on LiDAR point cloud data for autonomous vehicle projects. By leveraging spatial analysis and experience with AutoCAD, I accurately inferred object shapes even in challenging, noisy conditions. This enhanced the AI's spatial understanding and supported advanced perception tasks for safety-critical applications. • Delivered complex 3D object recognition in adverse environments. • Applied structural engineering concepts to spatial labeling. • Specialist in high-difficulty and high-precision LiDAR datasets. • Ensured volumetric accuracy for AI perception modules.

I executed high-precision 3D bounding box annotations on LiDAR point cloud data for autonomous vehicle projects. By leveraging spatial analysis and experience with AutoCAD, I accurately inferred object shapes even in challenging, noisy conditions. This enhanced the AI's spatial understanding and supported advanced perception tasks for safety-critical applications. • Delivered complex 3D object recognition in adverse environments. • Applied structural engineering concepts to spatial labeling. • Specialist in high-difficulty and high-precision LiDAR datasets. • Ensured volumetric accuracy for AI perception modules.

2023 - 2024

Data Annotation Specialist – Road Infrastructure Segmentation

CrowdsourceImageSegmentation

I conducted highly precise image segmentation for road infrastructure using rigorous pixel-level analysis. My process included maintaining a meticulous self-audit routine to differentiate complex boundaries and ensure accuracy. This work resulted in a rejection rate of less than 0.5% across tens of thousands of images, directly supporting AI models for autonomous driving and safety diagnostics. • Applied advanced segmentation techniques for lane boundaries and road features. • Managed large-scale annotation projects to deliver "zero-error" datasets. • Leveraged engineering standards developed from architectural training. • Ensured reliable ground truth data for high-stakes safety models.

I conducted highly precise image segmentation for road infrastructure using rigorous pixel-level analysis. My process included maintaining a meticulous self-audit routine to differentiate complex boundaries and ensure accuracy. This work resulted in a rejection rate of less than 0.5% across tens of thousands of images, directly supporting AI models for autonomous driving and safety diagnostics. • Applied advanced segmentation techniques for lane boundaries and road features. • Managed large-scale annotation projects to deliver "zero-error" datasets. • Leveraged engineering standards developed from architectural training. • Ensured reliable ground truth data for high-stakes safety models.

2021 - 2022

Data Annotation Specialist – Academic Paper Classification

Internal Proprietary ToolingDocumentClassification

I performed large-scale academic document classification for AI search engine training with a focus on contextual understanding. I analyzed thousands of research papers, proactively refining guidelines to improve ambiguity resolution and data integrity. This dedication produced a 99% accuracy rate and improved AI retrieval performance across complex information architectures. • Contextually classified academic text data for machine learning models. • Enhanced labeling guidelines to resolve subjective ambiguities. • Maintained high data integrity and low error rates. • Supported scalable information retrieval AI systems.

I performed large-scale academic document classification for AI search engine training with a focus on contextual understanding. I analyzed thousands of research papers, proactively refining guidelines to improve ambiguity resolution and data integrity. This dedication produced a 99% accuracy rate and improved AI retrieval performance across complex information architectures. • Contextually classified academic text data for machine learning models. • Enhanced labeling guidelines to resolve subjective ambiguities. • Maintained high data integrity and low error rates. • Supported scalable information retrieval AI systems.

2020 - 2021

Education

Work History