Peter A.

Key Skills

Software

Other

Micro1

Top Subject Matter

LLM response evaluation and dataset quality assurance

AI response labeling

Fact-checking Domain Expertise

Top Data Types

Text

Document

Top Task Types

Bounding Box

Polygon

RLHF

Fine-tuning

Question Answering

Text Generation

Freelancer Overview

Core strengths include Other and Micro1. Education includes Master of Science, University of the West of England and Bachelor of Engineering, Osun State University. AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

Outlier AI — AI Data Annotator (2025 – Present)

OtherText

Served as an AI Data Annotator by evaluating and annotating AI-generated responses for LLM training workflows. Applied complex annotation guidelines and rubric-based scoring to keep dataset quality and labeling consistency high. Reviewed outputs for factual accuracy, clarity, reasoning quality, and compliance with instructions. • Annotated reasoning, conversational outputs, and structured prompts • Scored responses using rubric-based frameworks • Flagged hallucinations, factual inaccuracies, and reasoning gaps • Provided structured feedback to support continuous model refinement

2025 - Present

Micro1 AI — Data Annotation Specialist (April 2025–December 2025)

Micro1Text

Performed data annotation for generative AI model training by labeling high-volume datasets and conducting quality assurance reviews. Applied structured annotation frameworks to identify subtle errors and dataset inconsistencies. Supported continuous improvement of AI response quality using systematic evaluation and feedback. • Completed high-volume dataset annotations for generative AI training • Conducted QA checks to find subtle labeling or content errors • Applied structured frameworks to maintain >97% labeling accuracy • Provided feedback based on evaluation results to improve outputs

2025 - 2025

Mindrift — Data Annotation Specialist (June 2024–November 2025)

OtherText

Worked as a Data Annotation Specialist supporting AI training by reviewing and labeling AI responses against detailed rubrics and quality standards. Collaborated with AI training workflows to improve response accuracy and ensure guideline adherence. Conducted fact-checking and contextual validation to detect inconsistencies and drive model improvements. • Applied evaluation rubrics and quality standards to labeled responses • Verified factuality through fact-checking and contextual validation • Detected inconsistencies and provided improvement feedback • Maintained precision and consistency on large annotation datasets

2024 - 2025

Education

Work History