Diego Ruben Chinga Nunez

Key Skills

Software

Clickworker

Remotasks

Scale AI

Other

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Text

Video

Top Task Types

Action Recognition

Audio Recording

Classification

Mapping

Prompt Response Writing SFT

Freelancer Overview

I have over 3 years of experience in AI training data projects and machine learning, specializing in data labeling, annotation, and quality review for diverse datasets, including text, images, and audio. My work has involved supporting international AI initiatives that required both accuracy and cultural nuance, particularly for Latin America, Africa, and Asia. Through these projects, I’ve developed strong skills in analyzing data patterns, identifying inconsistencies, and ensuring that datasets meet high-quality standards for model training. What sets me apart is my combination of technical expertise and community management experience. I have successfully led freelance and remote teams in AI-related projects, helping recruit and guide contributors while maintaining quality in large-scale data collection efforts. With a background in digital marketing, project management, and SAP system implementation, I bring an organized, detail-oriented, and results-driven approach to every project. My goal is always to deliver datasets that accelerate the development of accurate, inclusive, and impactful AI models.

Labeling Experience

Audio Data Collection

ClickworkerAudioData Collection

I participated in a large-scale audio data collection project with LXT, focused on supporting the training of Large Language Models (LLMs). My tasks involved recording and annotating high-quality voice samples in English and Spanish, ensuring clarity, consistency, and natural delivery. I followed strict project guidelines to meet accuracy and privacy standards, contributing to a dataset that powered speech recognition and natural language processing models. The project required careful attention to detail, time management, and adherence to quality measures such as reviewing submissions for background noise, pronunciation accuracy, and metadata correctness. By consistently meeting performance benchmarks, I helped deliver thousands of validated audio samples that improved the model’s ability to understand diverse accents and real-world speech patterns.

I participated in a large-scale audio data collection project with LXT, focused on supporting the training of Large Language Models (LLMs). My tasks involved recording and annotating high-quality voice samples in English and Spanish, ensuring clarity, consistency, and natural delivery. I followed strict project guidelines to meet accuracy and privacy standards, contributing to a dataset that powered speech recognition and natural language processing models. The project required careful attention to detail, time management, and adherence to quality measures such as reviewing submissions for background noise, pronunciation accuracy, and metadata correctness. By consistently meeting performance benchmarks, I helped deliver thousands of validated audio samples that improved the model’s ability to understand diverse accents and real-world speech patterns.

2024 - 2025

Education

Work History