Obasekam E.

Key Skills

Software

Don't disclose

Other

Top Subject Matter

Generative AI evaluation

LLM factual accuracy

semantic labeling

Top Data Types

Text

Document

Top Task Types

RLHF

Classification

Freelancer Overview

AI Data Trainer & Content Evaluator (Freelance / Crowdsourcing) — Remote (2025–Present). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Other. Education includes Bachelor of Science, University of Calabar (2023). AI-training focus includes data types such as Text and labeling workflows including RLHF and Classification.

Labeling Experience

AI Data Trainer & Content Evaluator (Freelance / Crowdsourcing) — Remote (2025–Present)

Don't discloseTextRLHF

Delivered AI training and evaluation work by formulating and refining prompts to stress-test generative models across multiple domains. Assessed AI outputs for factual accuracy, tone, helpfulness, and adherence to complex client constraints, then rewrote or ranked responses accordingly. Conducted high-volume annotation involving text segmentation and semantic labeling to improve downstream machine learning training datasets. • Prompt + response writing (SFT/RLHF-style) for model training and evaluation • Response ranking and rewriting based on strict guideline compliance • Semantic labeling and text segmentation for dataset quality • Human-in-the-loop style HITL feedback to maintain high accuracy

2025 - Present

Freelance Digital Task Specialist — Remote (2024–2025)

OtherTextClassification

Performed platform micro-tasks focused on organizing and validating web/search-relevance information for dataset or task curation. Conducted categorization and web research checks to ensure accurate labeling outcomes. Identified and reported edge cases, user interface issues, and data inconsistencies to improve data integrity and usability. • Search relevance assessment for classification/categorization tasks • Web research and categorization to support labeled outputs • Edge-case identification and reporting for quality improvements • Data inconsistency detection to maintain label integrity

2024 - 2025

Education

Work History