Al-Ameen A.

Key Skills

Software

Other

Top Subject Matter

AI and machine learning model training (text data)

Training and quality assurance (instructional tutoring)

Legal Services & Contract Review

Top Data Types

Computer Code Programming

Text

Image

Document

Top Task Types

Classification

Freelancer Overview

I am an AI Data Labeller with hands-on experience annotating text, conversational data, and other data types to support machine learning model training. I consistently follow detailed annotation guidelines to maintain accuracy and consistency across high volumes of data, and I apply a structured, methodical approach to identifying and escalating edge cases that could compromise dataset quality. My background in Python — including scripting, regular expressions, and web scraping using BeautifulSoup — gives me a technical understanding of how clean, well-labelled data feeds into AI pipelines, which helps me work with greater precision and contextual awareness than a non-technical labeller. What sets me apart is the combination of technical grounding and disciplined work habits. My Computer Engineering HND, Google IT Support certification, and ongoing Harvard CS50x programme reflect a commitment to continuous learning in the AI/tech space. My experience at PricewaterhouseCoopers — where accuracy, confidentiality, and process adherence were non-negotiable — directly mirrors the quality standards required in data labelling work. I am detail-oriented, self-directed, and comfortable working through repetitive, precision-critical tasks without compromising output quality.

Labeling Experience

AI Data Labeller — Independent/Contract (2026–Present)

Don't discloseTextClassification

Performed AI data labeling for machine learning model training using text-based annotations. Followed detailed annotation guidelines to maintain consistency and high accuracy across large volumes of data. Flagged ambiguous cases and escalated edge cases for quality review to preserve dataset integrity. • Annotated and labeled text data to support AI/ML training • Ensured guideline adherence for accuracy and consistency • Identified and escalated edge/ambiguous data points • Met throughput targets while sustaining accuracy

2026 - Present

Microsoft Office Instructor / Technical Tutor — Self-Employed (2024–Present)

Don't discloseText

Provided AI-adjacent instructional support by assessing learner outputs against defined benchmarks. Delivered structured, process-driven training sessions that mirrored quality assurance workflows. Documented observations and troubleshot issues to support consistent learning outcomes. • Assessed outputs using benchmark criteria • Applied structured instructional frameworks • Documented session notes and troubleshooting actions • Followed QA-like evaluation processes aligned to training practices

2024 - Present

Education

Work History