Brian Otieno

Key Skills

Software

Appen

Clickworker

CloudFactory

Labelbox

OneForma

Remotasks

SuperAnnotate

Toloka

Telus

Scale AI

Top Subject Matter

Natural Language Processing (NLP)

Data Labeling and Annotation

Content Development and Instructional Design

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Bounding Box

Data Collection

Evaluation Rating

Freelancer Overview

I am an experienced AI Trainer with a strong background in data annotation, machine learning, and natural language processing. Over the past several years, I have developed and implemented advanced training programs for AI models, focusing on optimizing their accuracy and performance through careful data analysis and evaluation. My expertise includes designing tailored annotation guidelines, evaluating model outputs, and troubleshooting training workflows to enhance AI capabilities. I have worked extensively with deep learning models and supervised learning strategies, particularly in the domain of language models, and have collaborated with cross-functional teams to ensure the delivery of high-quality, safe, and beneficial AI systems. With a foundation in both linguistics and computer science, I bring a detail-oriented and innovative approach to every project, continuously striving to improve AI training data quality and model reliability.

Labeling Experience

Data Labeler

Scale AIImageBounding BoxText Generation

I participated in a remote image annotation project for autonomous vehicle datasets using Remotasks. My primary responsibilities involved applying precise bounding boxes to identify and label objects such as vehicles, pedestrians, signage, and other road features across thousands of images. I adhered strictly to detailed project guidelines and quality standards, collaborating virtually with a global team of annotators and reviewers. The scope of the project required high accuracy and consistency to support machine learning development for advanced computer vision systems. My tasks included performing careful quality assurance, documenting workflows, and ensuring each annotated image met client requirements for use in autonomous vehicle safety and navigation algorithms.

I participated in a remote image annotation project for autonomous vehicle datasets using Remotasks. My primary responsibilities involved applying precise bounding boxes to identify and label objects such as vehicles, pedestrians, signage, and other road features across thousands of images. I adhered strictly to detailed project guidelines and quality standards, collaborating virtually with a global team of annotators and reviewers. The scope of the project required high accuracy and consistency to support machine learning development for advanced computer vision systems. My tasks included performing careful quality assurance, documenting workflows, and ensuring each annotated image met client requirements for use in autonomous vehicle safety and navigation algorithms.

2019 - 2022

Education

Work History