John M.

Key Skills

Software

Appen

AWS SageMaker

Top Subject Matter

LLM data annotation and AI response evaluation

AI project support via data preparation automation

Customer Support – AI Chatbot Response Writing & Quality Assurance

Top Data Types

Text

Image

Document

Top Task Types

Bounding Box

Segmentation

Entity (NER) Classification

Text Generation

Text Summarization

RLHF

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Freelancer Overview

AI Data Annotator & Trainer (Outlier AI, Remote). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Outlier and Don't disclose. Education includes Bachelor of Science in Industrial Chemistry, Federal University of Technology, Minna (2021) and Certificate, Government Science and Technical College Otukpa (2018). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Evaluation, Rating, and Computer Programming.

Labeling Experience

IT Support & Digital Specialist (Freelance / Academic Projects)

Don't disclose

Used Python to automate repetitive data organization tasks for academic and freelance AI-related projects. Assisted with technical workflows that support data preparation for AI use cases. Followed established procedures to improve efficiency and reduce manual effort during data handling. • Built or ran Python scripts for organizing datasets • Supported project-level preparation of structured data • Reduced errors through automated data handling • Collaborated in academic project execution workflows

2024 - Present

AI Data Annotator & Trainer (Outlier AI, Remote)

Text

Annotated and labeled large-scale datasets for text-based AI models while ensuring 95%+ accuracy across assigned tasks. Evaluated AI-generated responses for factual accuracy, relevance, and tone according to provided guidelines. Documented annotation outcomes and quality checks to support downstream model training and improvement. • Worked with prompt and response evaluation criteria • Applied guideline adherence to maintain dataset consistency • Performed quality control on labeling outputs • Supported preparation of training-ready examples

2025 - 2025

Education

Work History