Dennis Kim

Key Skills

Software

Labelbox

CVAT

LabelImg

Other

Top Subject Matter

Autonomous Driving

E-Commerce and Medical NLP

Retail Product Recognition and Speech-to-Text

Top Data Types

Image

Text

Audio

Document

Top Task Types

Bounding Box

Entity (NER) Classification

Object Detection

Transcription

Segmentation

Freelancer Overview

Senior Data Operations Specialist. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, CVAT, and LabelImg. Education includes Bachelor of Science, University of Nairobi (2019). AI-training focus includes data types such as Image, Text, and Audio and labeling workflows including Bounding Box, Entity (NER) Classification, and Object Detection.

Labeling Experience

Senior Data Operations Specialist

LabelboxImageBounding Box

Led a team of annotators in labeling image data for an autonomous driving AI project. Developed and refined detailed labeling manuals while maintaining rigorous quality standards. Automated QA processes with Python scripts to ensure exceptional labeling accuracy. • Managed edge-case handling in annotation workflows. • Collaborated with machine learning engineers for taxonomy updates. • Delivered annotations using tools such as Labelbox and CVAT. • Ensured project completion with 99%+ accuracy across large datasets.

Led a team of annotators in labeling image data for an autonomous driving AI project. Developed and refined detailed labeling manuals while maintaining rigorous quality standards. Automated QA processes with Python scripts to ensure exceptional labeling accuracy. • Managed edge-case handling in annotation workflows. • Collaborated with machine learning engineers for taxonomy updates. • Delivered annotations using tools such as Labelbox and CVAT. • Ensured project completion with 99%+ accuracy across large datasets.

2023 - Present

Data Labeling Lead

CVATTextEntity Ner Classification

Oversaw NLP data labeling projects, focusing on intent classification and named entity recognition for e-commerce data. Conducted extensive audits and coaching to maintain high annotation accuracy. Utilized CVAT and LabelImg to segment medical images for health-tech AI projects. • Managed high throughput of dataset labeling. • Improved annotation standardization for medical imagery. • Optimized raw data ingestion for labeling environments. • Maintained a consistent accuracy rate above 98%.

Oversaw NLP data labeling projects, focusing on intent classification and named entity recognition for e-commerce data. Conducted extensive audits and coaching to maintain high annotation accuracy. Utilized CVAT and LabelImg to segment medical images for health-tech AI projects. • Managed high throughput of dataset labeling. • Improved annotation standardization for medical imagery. • Optimized raw data ingestion for labeling environments. • Maintained a consistent accuracy rate above 98%.

2021 - 2022

Junior Data Associate

LabelimgImageObject Detection

Labeled retail images for AI model training, focusing on product identification and brand logo detection. Created ground-truth datasets as part of cross-functional Golden Set initiatives. Provided detailed documentation for speech-to-text and vision data annotation projects. • Annotated 100,000+ unique data points for computer vision models. • Ensured data quality and addressed cultural nuances in labeling. • Worked closely with engineering teams on model requirements. • Participated in benchmarking efforts for accuracy assurance.

Labeled retail images for AI model training, focusing on product identification and brand logo detection. Created ground-truth datasets as part of cross-functional Golden Set initiatives. Provided detailed documentation for speech-to-text and vision data annotation projects. • Annotated 100,000+ unique data points for computer vision models. • Ensured data quality and addressed cultural nuances in labeling. • Worked closely with engineering teams on model requirements. • Participated in benchmarking efforts for accuracy assurance.

2019 - 2021

Agricultural Satellite Imagery Project Contributor

OtherSegmentation

Applied semantic segmentation to satellite imagery to assess crop health and drought conditions in East Africa. Contributed to humanitarian aid allocation models by producing pixel-accurate classified maps. Handled geospatial annotation tasks with attention to agricultural domain standards. • Identified regions of interest based on visual crop features. • Annotated satellite images for land cover classification. • Ensured labeling complied with agricultural modeling requirements. • Produced datasets for AI-driven allocation optimization.

Applied semantic segmentation to satellite imagery to assess crop health and drought conditions in East Africa. Contributed to humanitarian aid allocation models by producing pixel-accurate classified maps. Handled geospatial annotation tasks with attention to agricultural domain standards. • Identified regions of interest based on visual crop features. • Annotated satellite images for land cover classification. • Ensured labeling complied with agricultural modeling requirements. • Produced datasets for AI-driven allocation optimization.

Not specified

Audio Annotation Project Contributor

OtherAudioTranscription

Curated and annotated over 500 hours of Swahili and Sheng audio data for regional dialect recognition. Supported a global tech client in improving the accuracy of voice assistants targeting East African populations. Ensured precise transcription and dialect classification through manual annotation techniques. • Focused on speech recognition for local dialect accuracy. • Provided linguistic QA for annotated audio files. • Maintained compliance with language-specific guidelines. • Collaborated with global engineers for dataset validation.

Curated and annotated over 500 hours of Swahili and Sheng audio data for regional dialect recognition. Supported a global tech client in improving the accuracy of voice assistants targeting East African populations. Ensured precise transcription and dialect classification through manual annotation techniques. • Focused on speech recognition for local dialect accuracy. • Provided linguistic QA for annotated audio files. • Maintained compliance with language-specific guidelines. • Collaborated with global engineers for dataset validation.

Not specified

Education

Work History