Williams Joshua

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Image

Top Label Types

Polygon

Point Key Point

Object Detection

Freelancer Overview

I am a detail-oriented professional with over six years of experience in reviewing and evaluating complex technical and narrative content, with a strong focus on AI output evaluation and data annotation. My expertise includes rubric-based scoring, response comparison, and quality assessment within human-in-the-loop workflows, making me highly proficient in the structured review processes essential for AI training data pipelines. I excel at identifying nuanced errors in grammar, tone, logic, and factual accuracy, providing clear and actionable feedback to ensure content meets strict standards and guidelines. My background has equipped me to manage high-volume review tasks independently, optimize clarity and consistency, and contribute to the continuous improvement of AI-generated content, particularly in natural language processing and related domains. I am comfortable working remotely and thrive in environments that demand objective judgment, precision, and a commitment to data quality.

Labeling Experience

Data annotator and labler

Scale AIImagePolygonPoint Key Point

Automotive and traffic image annotation project focused on training computer vision models for object detection and spatial recognition. Responsible for labeling vehicles, pedestrians, road signs, traffic lights, and other roadway elements using polygon, key point, and object detection techniques. Ensured high-quality annotations by carefully following project guidelines and reviewing edge cases to maintain consistency and accuracy across large image datasets. Worked within the Remotasks platform to complete high-volume labeling tasks while meeting strict quality control standards and project requirements.

Automotive and traffic image annotation project focused on training computer vision models for object detection and spatial recognition. Responsible for labeling vehicles, pedestrians, road signs, traffic lights, and other roadway elements using polygon, key point, and object detection techniques. Ensured high-quality annotations by carefully following project guidelines and reviewing edge cases to maintain consistency and accuracy across large image datasets. Worked within the Remotasks platform to complete high-volume labeling tasks while meeting strict quality control standards and project requirements.

2023 - 2025

Education

Work History