Antony Munyao

Key Skills

Software

Label Studio

AWS SageMaker

Datasaur

Snorkel AI

Top Subject Matter

No subject matter listed

Top Data Types

Text

Image

Top Label Types

RLHF

Object Detection

Entity Ner Classification

Freelancer Overview

I am an experienced AI data labeler and trainer with over five years working on diverse projects in data annotation, model evaluation, and RLHF. My background includes leading labeling for large language models, annotating more than 50,000 images and videos for computer vision in medical imaging and satellite data, and managing multilingual teams for global clients. I am skilled in using tools like Label Studio, Argilla, AWS SageMaker, CVAT, and SuperAnnotate, and have a strong foundation in Python for data quality assurance. My work spans technical, medical, legal, and creative domains, and I am passionate about ensuring high-quality, accurate training data to power advanced AI systems. I thrive in collaborative environments and am committed to delivering precise, reliable results for every project.

Labeling Experience

Data Annotation Specialist – Computer Vision (Freelance)

Aws SagemakerImageObject Detection

Annotated over 50,000 images and videos targeting computer vision solutions in medical imaging and satellite data. Integrated with AWS SageMaker and CVAT to handle large-scale annotation projects efficiently. Ensured accurate data labeling according to domain-specific project guides. • Labeled medical/DICOM and geospatial/satellite images for object detection and classification. • Used AWS SageMaker and CVAT for annotation, workflow management, and QA. • Managed labeling scale for diverse computer vision tasks spanning multiple industries. • Delivered high-quality, structured annotations to support AI model training and evaluation.

Annotated over 50,000 images and videos targeting computer vision solutions in medical imaging and satellite data. Integrated with AWS SageMaker and CVAT to handle large-scale annotation projects efficiently. Ensured accurate data labeling according to domain-specific project guides. • Labeled medical/DICOM and geospatial/satellite images for object detection and classification. • Used AWS SageMaker and CVAT for annotation, workflow management, and QA. • Managed labeling scale for diverse computer vision tasks spanning multiple industries. • Delivered high-quality, structured annotations to support AI model training and evaluation.

2022

Data Annotation Specialist – LLM, RLHF, Red Teaming, QA (Freelance)

Label StudioTextRLHF

Led data labeling for multiple LLM projects, including red teaming, supervised fine-tuning, and structured evaluations. Conducted RLHF sessions to improve model performance, maintaining 95% accuracy in quality assessment. Provided feedback on over 1,000 interactions, with experience in multilingual team and client environments. • Utilized Label Studio and Argilla for text annotation, evaluation, and model training. • Managed teams annotating English, Swahili, and French data for global AI startups. • Ensured compliance with project-specific rubrics and data integrity. • Worked with LLM red teaming, supervised fine-tuning, and evaluation tasks.

Led data labeling for multiple LLM projects, including red teaming, supervised fine-tuning, and structured evaluations. Conducted RLHF sessions to improve model performance, maintaining 95% accuracy in quality assessment. Provided feedback on over 1,000 interactions, with experience in multilingual team and client environments. • Utilized Label Studio and Argilla for text annotation, evaluation, and model training. • Managed teams annotating English, Swahili, and French data for global AI startups. • Ensured compliance with project-specific rubrics and data integrity. • Worked with LLM red teaming, supervised fine-tuning, and evaluation tasks.

2022

Machine Learning Intern – Text and Audio Annotation

DatasaurTextEntity Ner Classification

Assisted in data preprocessing and labeling for NLP models with multilingual text annotation. Performed quality assurance checks, reducing errors significantly via custom scripting and careful review. Contributed to speech/audio labeling and document segmentation projects. • Labeled datasets in five languages to enhance NLP model capabilities. • Applied classification and NER tasks using Python tools in the pipeline. • Participated in error-reduction through systematic dataset reviews. • Worked with speech/audio labeling, document segmentation, and dataset standardization.

Assisted in data preprocessing and labeling for NLP models with multilingual text annotation. Performed quality assurance checks, reducing errors significantly via custom scripting and careful review. Contributed to speech/audio labeling and document segmentation projects. • Labeled datasets in five languages to enhance NLP model capabilities. • Applied classification and NER tasks using Python tools in the pipeline. • Participated in error-reduction through systematic dataset reviews. • Worked with speech/audio labeling, document segmentation, and dataset standardization.

2020 - 2022

Research Assistant – Scientific Data Annotation

Snorkel AITextEntity Ner Classification

Supported AI research by labeling datasets for technical and scientific subject matter. Participated in red teaming and ethical AI review exercises to identify vulnerabilities and ensure robust model development. Integrated PubChem and BioPython datasets to facilitate advanced AI research projects. • Conducted scientific and technical dataset annotation with emphasis on accuracy. • Engaged in ethical AI labeling, red teaming, and documentation. • Integrated and labeled chemical/biological data using specialized tools. • Facilitated data quality control and labeling for university research teams.

Supported AI research by labeling datasets for technical and scientific subject matter. Participated in red teaming and ethical AI review exercises to identify vulnerabilities and ensure robust model development. Integrated PubChem and BioPython datasets to facilitate advanced AI research projects. • Conducted scientific and technical dataset annotation with emphasis on accuracy. • Engaged in ethical AI labeling, red teaming, and documentation. • Integrated and labeled chemical/biological data using specialized tools. • Facilitated data quality control and labeling for university research teams.

2018 - 2020

Education

Work History