Kim Webi

Key Skills

Software

Mercor

CVAT

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Text

Image

Video

Computer Code Programming

Top Label Types

Entity Ner Classification

Question Answering

Text Generation

Text Summarization

Evaluation Rating

Bounding Box

Polygon

Segmentation

Action Recognition

Tracking

Routing

Computer Programming Coding

Function Calling

Freelancer Overview

I have 1–3 years of hands-on experience in data labeling and AI training data, working on image, text, and audio annotation projects to support machine learning and computer vision models. My work includes tasks such as creating bounding boxes and performing polygon and semantic segmentation and executing keypoint annotation and executing NLP labeling which includes sentiment analysis and intent classification and named entity recognition. I maintain accurate annotation results because I follow complete annotation guidelines during quality assurance checks. I am proficient with industry-standard annotation tools and platforms and have experience reviewing and correcting annotations to meet strict quality benchmarks. I demonstrate strong attention to detail, I maintain consistent work output, and I can work independently in remote settings while quickly adapting to new project requirements. My ability to deliver high-quality labeled data on time helps ensure reliable model training and overall project success.

Labeling Experience

Data Annotation Quality Assurance & Review (NDA-Protected)

MercorComputer Code ProgrammingTrackingRouting

The project uses Text and Image and Video data as its primary information source for programming. The project focuses on AI Training Data and Machine Learning as its primary research area. The QA reviewer role required me to assess codes and programs for different systems and functions. My duties required me to validate the code while fixing mistakes and checking for guideline compliance and giving feedback to the annotators. Our team achieved high dataset accuracy which we maintained until the project reached its final stage for AI model training delivery.

The project uses Text and Image and Video data as its primary information source for programming. The project focuses on AI Training Data and Machine Learning as its primary research area. The QA reviewer role required me to assess codes and programs for different systems and functions. My duties required me to validate the code while fixing mistakes and checking for guideline compliance and giving feedback to the annotators. Our team achieved high dataset accuracy which we maintained until the project reached its final stage for AI model training delivery.

2025 - 2025

Video Annotation Project

AppenVideoBounding BoxAction Recognition

Created annotated video datasets which show all frames for object detection and tracking purposes. Preserved temporal consistency between all frames while labeling moving objects and actions. Also created video annotations which met essential quality standards to enable training of machine learning models that use video data.

Created annotated video datasets which show all frames for object detection and tracking purposes. Preserved temporal consistency between all frames while labeling moving objects and actions. Also created video annotations which met essential quality standards to enable training of machine learning models that use video data.

2023 - 2024

Image Annotation for Computer Vision Models (NDA-Protected)

CVATImageBounding BoxPolygon

We as a team performed image annotation work which included object detection and segmentation tasks across multiple datasets. We had to create precise bounding boxes and polygons for object annotation while following strict guidelines. We maintained high precision and consistency standards which enabled us to produce dependable results for training computer vision models. We also used quality assurance feedback as a basis for our work to enhance annotation standards.

We as a team performed image annotation work which included object detection and segmentation tasks across multiple datasets. We had to create precise bounding boxes and polygons for object annotation while following strict guidelines. We maintained high precision and consistency standards which enabled us to produce dependable results for training computer vision models. We also used quality assurance feedback as a basis for our work to enhance annotation standards.

2023 - 2024

Text Annotation Project (NDA-Protected)

MercorTextEntity Ner ClassificationQuestion Answering

I participated in several large-scale confidential text annotation projects which provided support for natural language processing development and large language model training. The team accomplished multiple tasks which required them to label text using named entity recognition and sentiment analysis and emotion detection and intent classification and question answering validation and content assessment. The team followed annotation guidelines to complete their work while meeting all quality standards through internal quality assurance processes. The AI models used the annotated data to enhance their language comprehension abilities and their capacity to generate accurate responses.

I participated in several large-scale confidential text annotation projects which provided support for natural language processing development and large language model training. The team accomplished multiple tasks which required them to label text using named entity recognition and sentiment analysis and emotion detection and intent classification and question answering validation and content assessment. The team followed annotation guidelines to complete their work while meeting all quality standards through internal quality assurance processes. The AI models used the annotated data to enhance their language comprehension abilities and their capacity to generate accurate responses.

2023 - 2023

Education

Work History