Muhammad Abdullah

Key Skills

Software

Data Annotation Tech

Dataloop

Humanatic

OneForma

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Text

Video

Top Task Types

Audio Recording

Computer Programming Coding

Data Collection

Translation Localization

Freelancer Overview

With over three years of hands-on experience in data labeling and AI training, I have developed strong skills in annotating diverse datasets, including text, audio, and images. My work with companies like IN TECH SOLUTIONS involved accurately tagging language and image data to improve machine learning models, while my role at HUMANATIC focused on call content review, enhancing AI-driven voice recognition systems. I am proficient in using tools such as Python, Excel, and ChatGPT to analyze and optimize training data, ensuring high-quality and reliable AI outputs. My multilingual proficiency in English, Urdu, Pashto, Arabic, and Hindi allows me to contribute effectively to projects requiring linguistic diversity and nuanced understanding. Coupled with meticulous attention to detail and logical reasoning, I have consistently delivered precise annotations that empower AI models to perform better across various industries. My passion for AI and dedication to quality make me a valuable contributor to any AI training data project.

Labeling Experience

Multilingual Chatbot Text Annotation for AI Training

AppenAudioClassificationText Generation

Labeled text and audio samples in English, Urdu, Pashto, Arabic, and Hindi to enhance chatbot understanding and voice recognition models. Tasks included classifying intent, reviewing sentiment, and evaluating speech accuracy. Delivered high-precision annotations for datasets exceeding 10,000 samples; quality audited with 98% accuracy.

Labeled text and audio samples in English, Urdu, Pashto, Arabic, and Hindi to enhance chatbot understanding and voice recognition models. Tasks included classifying intent, reviewing sentiment, and evaluating speech accuracy. Delivered high-precision annotations for datasets exceeding 10,000 samples; quality audited with 98% accuracy.

2022 - 2023

Education

Work History