Doris Nzioki

Key Skills

Software

CloudFactory

Mindrift

OneForma

Remotasks

Scale AI

Toloka

CVAT

Top Subject Matter

Academic Writing and Research

Programming Language Tutoring and ICT Consultancy

Web Development and Software Engineering

Top Data Types

Image

Text

Video

Top Task Types

Bounding Box

Computer Programming Coding

Prompt Response Writing SFT

Text Generation

Text Summarization

Freelancer Overview

As an experienced professional in data labeling and AI training, I bring over 5 years of expertise in various industries, including academic writing, programming education, and ICT consultancy. My work has involved producing high-quality labeled datasets for machine learning models, particularly in natural language processing (NLP) and computer vision applications. I have a proven track record in developing and delivering comprehensive programming courses, providing consultancy on ICT infrastructure, and crafting engaging and contextually accurate responses for AI chatbot platforms. My key skills include data annotation, transcription, and creative writing, with proficiency in tools like Labelbox, CVAT, and SuperAnnotate. I have successfully completed projects such as the development of a web platform for Sign Gate Inc. in Rwanda, showcasing my ability to integrate secure systems and implement responsive designs. Fluent in multiple languages, including English, Kiswahili, French, and Spanish, I possess strong editing and proofreading skills, ensuring high-quality outputs. My commitment to continuous learning and professional development sets me apart as a versatile and dedicated professional in the AI training and data labeling field.

Labeling Experience

Autonomous Vehicle Data Annotation Specialist

CVATImagePolygonCuboid

This project involved annotating a large dataset of images, videos, and LiDAR sensor data for an autonomous vehicle technology company. The primary focus was on accurately labeling various objects such as vehicles, pedestrians, traffic signs, and road markings to train machine learning models for object detection and tracking. Tasks included creating bounding boxes, polygons, and 3D cuboids, as well as performing semantic segmentation to classify different areas within the environment. The project adhered to strict quality standards, with regular cross-verification and auditing processes to ensure high accuracy and consistency. Over 50,000 images and videos were annotated, significantly contributing to the development of the company's autonomous driving system.

This project involved annotating a large dataset of images, videos, and LiDAR sensor data for an autonomous vehicle technology company. The primary focus was on accurately labeling various objects such as vehicles, pedestrians, traffic signs, and road markings to train machine learning models for object detection and tracking. Tasks included creating bounding boxes, polygons, and 3D cuboids, as well as performing semantic segmentation to classify different areas within the environment. The project adhered to strict quality standards, with regular cross-verification and auditing processes to ensure high accuracy and consistency. Over 50,000 images and videos were annotated, significantly contributing to the development of the company's autonomous driving system.

2021 - 2023

Education

Work History