Alice Nyoike

Key Skills

Software

CVAT

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Polygon

Segmentation

Freelancer Overview

I am a detail-oriented AI Training Specialist with hands-on experience in data labeling, annotation, and evaluation for AI and machine learning workflows, particularly in natural language processing. My background includes completing structured tasks such as data review, content validation, and quality checks, as well as evaluating AI-generated responses for accuracy, relevance, and compliance with complex instructions. I have developed strong skills in instruction analysis, logical reasoning, and consistency through online technical training in Python, data science, and machine learning. My recent projects involved improving large language model performance by assessing and rewriting AI responses for clarity and adherence to guidelines. I am committed to delivering high-quality, reliable training data that supports the development of advanced AI models.

Labeling Experience

High-Precision Object Detection & Segmentation for Autonomous Driving Data

CVATImagePolygonSegmentation

Labeled and annotated large-scale image and video datasets for autonomous driving applications, focusing on urban traffic environments. Tasks included drawing high-accuracy bounding boxes and polygon masks for vehicles, pedestrians, cyclists, traffic signs, and lane markings, as well as frame-to-frame object tracking. Worked on datasets exceeding 150,000 images and 2,000+ video clips. Followed strict annotation guidelines to ensure spatial accuracy, class consistency, and temporal stability. Participated in multi-stage quality assurance workflows, including peer reviews and audit corrections, maintaining an average annotation accuracy rate above 98%.

Labeled and annotated large-scale image and video datasets for autonomous driving applications, focusing on urban traffic environments. Tasks included drawing high-accuracy bounding boxes and polygon masks for vehicles, pedestrians, cyclists, traffic signs, and lane markings, as well as frame-to-frame object tracking. Worked on datasets exceeding 150,000 images and 2,000+ video clips. Followed strict annotation guidelines to ensure spatial accuracy, class consistency, and temporal stability. Participated in multi-stage quality assurance workflows, including peer reviews and audit corrections, maintaining an average annotation accuracy rate above 98%.

2025 - 2025

Education

Work History