Dennis Muthama

Key Skills

Software

Labelbox

CVAT

SuperAnnotate

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Top Label Types

Bounding Box

Entity Ner Classification

Classification

Freelancer Overview

I am an AI training specialist with over 3 years of hands-on experience in data labeling, annotation, and dataset preparation for computer vision, natural language processing, and audio AI projects. My expertise includes creating high-quality labeled datasets using tools like Labelbox, CVAT, and YOLO-based workflows, with a proven track record of maintaining over 98% accuracy across large-scale annotation projects. I am skilled in a wide range of annotation tasks, including bounding boxes, segmentation, object tracking, sentiment and intent classification, and speech transcription. I have contributed to the development and validation of datasets for autonomous systems, surveillance, and speech recognition models, always ensuring strict adherence to annotation guidelines and quality standards. My technical background in Python and machine learning workflows allows me to effectively support AI model training pipelines and collaborate remotely with global teams to deliver reliable, production-ready training data.

Labeling Experience

AI Training & Data Annotation Specialist

LabelboxImageBounding Box

Oversaw detailed annotation of large-scale image and video datasets for AI model training in computer vision and NLP applications. Utilized a variety of labeling techniques such as bounding boxes, polygons, and segmentation masks for object detection and tracking tasks. Ensured precise quality control of dataset labeling, enforcing high accuracy and compliance with established annotation guidelines. • Supported labeling for autonomous system and surveillance model pipelines. • Conducted quality control reviews with structured feedback to enhance dataset consistency and model accuracy. • Maintained labeling accuracy above 98% across multiple annotation projects. • Annotated over 150,000 images and frames to support model performance improvements.

Oversaw detailed annotation of large-scale image and video datasets for AI model training in computer vision and NLP applications. Utilized a variety of labeling techniques such as bounding boxes, polygons, and segmentation masks for object detection and tracking tasks. Ensured precise quality control of dataset labeling, enforcing high accuracy and compliance with established annotation guidelines. • Supported labeling for autonomous system and surveillance model pipelines. • Conducted quality control reviews with structured feedback to enhance dataset consistency and model accuracy. • Maintained labeling accuracy above 98% across multiple annotation projects. • Annotated over 150,000 images and frames to support model performance improvements.

2023

Data Annotation Specialist

CVATTextEntity Ner Classification

Labeled and structured diverse datasets, including text, image, and audio, for machine learning pipelines supporting various AI models. Performed speech-to-text transcription, sentiment analysis, intent classification, and data organization using collaborative annotation tools. Collaborated with QA teams to uphold high-quality labeling standards and dataset integrity. • Carried out sentiment and intent classification for natural language understanding models. • Executed audio tagging and transcription for speech recognition development. • Reviewed and exported annotated datasets using dedicated platforms. • Ensured collaborative quality assurance with review team feedback.

Labeled and structured diverse datasets, including text, image, and audio, for machine learning pipelines supporting various AI models. Performed speech-to-text transcription, sentiment analysis, intent classification, and data organization using collaborative annotation tools. Collaborated with QA teams to uphold high-quality labeling standards and dataset integrity. • Carried out sentiment and intent classification for natural language understanding models. • Executed audio tagging and transcription for speech recognition development. • Reviewed and exported annotated datasets using dedicated platforms. • Ensured collaborative quality assurance with review team feedback.

2022 - 2022

Junior AI Data Annotator

SuperannotateImageClassification

Supported preparation and annotation of foundational AI datasets with a particular emphasis on image classification and object labeling tasks. Maintained annotation consistency by following strict labeling guidelines and participating in feedback loops to refine dataset accuracy. Assisted with initial dataset structuring activities for subsequent deep learning training. • Performed image classification and object labeling for training pipelines. • Ensured strict guideline compliance during annotation. • Contributed to feedback cycles for error and ambiguity detection in labeled data. • Supported model development by preparing training-ready datasets.

Supported preparation and annotation of foundational AI datasets with a particular emphasis on image classification and object labeling tasks. Maintained annotation consistency by following strict labeling guidelines and participating in feedback loops to refine dataset accuracy. Assisted with initial dataset structuring activities for subsequent deep learning training. • Performed image classification and object labeling for training pipelines. • Ensured strict guideline compliance during annotation. • Contributed to feedback cycles for error and ambiguity detection in labeled data. • Supported model development by preparing training-ready datasets.

2021 - 2022

Education

Work History