Philip King'oo

Key Skills

Software

Appen

Clickworker

CrowdSource

Data Annotation Tech

LabelImg

Label Studio

Remotasks

Scale AI

Toloka

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Video

Top Task Types

Computer Programming Coding

Data Collection

Evaluation Rating

Prompt Response Writing SFT

RLHF

Freelancer Overview

I have worked for three years as a data labeler. I have worked with Remotasks, Outlier, and Telus International on many kinds of jobs. I know a lot about handling words with AI (NLP), seeing with computers, and AI help for users. I focus on marking words, cutting up images, and checking chat replies. I have marked more than 5,000 data bits, made up of over 3,000 word sets for feeling checks and over 2,000 images to spot objects, with an accuracy of more than 98%. I am good at using tools like Label Studio, CVAT, and AWS SageMaker. I am great at making top notch data sets for AI learning, even with tight time limits. I know both English and Swahili well, helping me to work on jobs in many languages. My degree in Computer Science from Mount Kenya University has given me strong skills for handling data well before it is used and making sure it is of high quality. What makes me stand out is how I focus on small details, can change as needed, and work hard to make AI better by making very exact marks and learning from what humans say (RLHF). I have worked on key jobs like making AI chats make more sense, and helping make data for self driving cars, making sure the AI answers are strong and can be trusted. My mix of strong tech skills, knowing many languages, and a history of success makes me a great pick for OpenTrain AI's needs for different jobs.

Labeling Experience

Image Annotation for Medical Imaging AI

TelusImageEntity Ner Classification

I spearheaded the annotation of 3,000+ medical images (X-rays and MRIs) for a healthcare AI project aimed at improving diagnostic accuracy for lung and brain conditions. Using CVAT, I performed precise semantic segmentation and bounding box labeling to identify abnormalities, achieving a 97% accuracy rate after rigorous quality checks. My role involved collaborating with a global team of 15 labelers to standardize annotations and meet a 10-week deadline, contributing to a 20% improvement in the AI model’s detection precision. Leveraging my Computer Science background, I utilized Python scripts to preprocess image data, streamlining the annotation workflow. My fluency in English and Swahili, combined with proficiency in CVAT and Label Studio, ensured high-quality, culturally sensitive deliverables. This project underscores my expertise in computer vision and my ability to deliver accurate datasets for critical AI applications, making me a strong fit for OpenTrain AI’s healthcare and ima

I spearheaded the annotation of 3,000+ medical images (X-rays and MRIs) for a healthcare AI project aimed at improving diagnostic accuracy for lung and brain conditions. Using CVAT, I performed precise semantic segmentation and bounding box labeling to identify abnormalities, achieving a 97% accuracy rate after rigorous quality checks. My role involved collaborating with a global team of 15 labelers to standardize annotations and meet a 10-week deadline, contributing to a 20% improvement in the AI model’s detection precision. Leveraging my Computer Science background, I utilized Python scripts to preprocess image data, streamlining the annotation workflow. My fluency in English and Swahili, combined with proficiency in CVAT and Label Studio, ensured high-quality, culturally sensitive deliverables. This project underscores my expertise in computer vision and my ability to deliver accurate datasets for critical AI applications, making me a strong fit for OpenTrain AI’s healthcare and ima

2022 - 2023

Education

Work History