Josh Kim

Key Skills

Software

AWS SageMaker

Appen

Argilla

Clickworker

CloudFactory

Remotasks

Scale AI

Top Subject Matter

Healthcare and Medical annotation

Autonomous Vehicles mapping

LLM evaluation in English

Top Data Types

Computer Code Programming

Image

Medical Dicom

Top Task Types

Bounding Box

Classification

Computer Programming Coding

Mapping

Prompt Response Writing SFT

Freelancer Overview

With over five years of experience in data labeling and AI training data annotation, I have developed a deep expertise in creating high-quality annotated datasets for various industries such as healthcare, autonomous vehicles, retail, finance, and more. My precision data labeling skills have been instrumental in enhancing the accuracy and performance of AI and machine learning models, enabling clients to achieve their desired outcomes efficiently and effectively. I have successfully managed and executed numerous data labeling projects, utilizing industry-specific knowledge and subject matter expertise to ensure the thorough and accurate annotation of datasets. My ability to understand and interpret complex data requirements, combined with my attention to detail and commitment to quality, has earned me a reputation as a trusted partner in the AI training data space. Additionally, my familiarity with various annotation tools and techniques, coupled with a track record of delivering projects on time and within budget, distinguishes me as a valuable asset in the field of data labeling and AI training data annotation.

Labeling Experience

Autonomous Vehicle Training Data

Scale AIVideoBounding BoxPolygon

The scope of the project was to accurately label objects in images and videos to support the development of computer vision models for autonomous driving systems. The specific data labeling tasks performed included identifying and annotating various objects such as pedestrians, vehicles, traffic signs, and road markings in different driving scenarios. The project was extensive in size, with millions of images and videos to be annotated to train the AI algorithms effectively. Quality measures were a top priority in this project, and we adhered to strict guidelines to ensure the accuracy and consistency of the annotations. We implemented a multi-step quality control process, which included multiple rounds of annotation by different annotators, as well as a final review by senior annotators to ensure the highest level of data quality. Additionally, we utilized annotation tools that provided real-time feedback to annotators to minimize errors and ensure the precision of the labeled data.

The scope of the project was to accurately label objects in images and videos to support the development of computer vision models for autonomous driving systems. The specific data labeling tasks performed included identifying and annotating various objects such as pedestrians, vehicles, traffic signs, and road markings in different driving scenarios. The project was extensive in size, with millions of images and videos to be annotated to train the AI algorithms effectively. Quality measures were a top priority in this project, and we adhered to strict guidelines to ensure the accuracy and consistency of the annotations. We implemented a multi-step quality control process, which included multiple rounds of annotation by different annotators, as well as a final review by senior annotators to ensure the highest level of data quality. Additionally, we utilized annotation tools that provided real-time feedback to annotators to minimize errors and ensure the precision of the labeled data.

2020 - 2023

Education

Work History