Xame D.

Key Skills

Software

Other

Top Subject Matter

Conversational AI

LLM response evaluation

and RLHF feedback collection

Top Data Types

Text

Audio

Image

Document

Top Task Types

RLHF

Transcription

Data Collection

Freelancer Overview

AI Trainer & Data Labeling Specialist (Freelance / Multiple Platforms). Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other. Education includes Bachelor of Science, University of Ibadan (2025) and Bachelor of Science, SQI College of ICT (2025). AI-training focus includes data types such as Text and Audio and labeling workflows including RLHF, Transcription, and Data Collection.

Labeling Experience

AI Trainer & Annotation Expert (Freelance / Multiple Platforms)

OtherAudioTranscription

Annotated audio data via transcription and tagging for dataset creation and downstream NLP tasks. Applied consistent labeling standards to improve dataset quality, label reliability, and model training readiness. Coordinated ambiguity handling using guideline-based decisions and reviewer escalation when needed. • Audio transcription and transcription-related tagging • Consistent guideline adherence to improve label reliability • Flagging ambiguous cases for reviewer resolution • Quality-focused dataset preparation for training workflows

2023 - Present

AI Trainer & Data Labeling Specialist (Freelance / Multiple Platforms)

OtherTextRLHF

Provided human feedback for reinforcement learning from human feedback (RLHF) by ranking, rating, and rewriting AI-generated responses. Documented hallucinations, safety/policy violations, and reasoning errors with structured justifications to support model fine-tuning. Followed strict annotation guidelines to ensure consistent and actionable training signals. • RLHF ranking and rating of LLM outputs • Response rewriting to improve helpfulness, safety, and factual accuracy • Structured error reports for fine-tuning teams • Adversarial prompt testing and red-team findings

2023 - Present

Software Engineering Instructor (Annotation-Aware AI/ML Training)

OtherTextData Collection

Trained students on AI/ML fundamentals with a focus on annotation-aware workflows. Delivered instruction on supervised learning, data pipelines, and annotation best practices, then reinforced concepts through reproducible labeling and evaluation labs. Helped learners understand inter-annotator agreement and quality assurance considerations that affect model performance. • AI/ML training for supervised learning and data pipelines • Manual labeling practice and guideline application • Evaluation of model predictions using labeled datasets • Training on inter-annotator agreement and dataset QA

2022 - Present

Education

Work History