Bisi V.

Key Skills

Software

Other

Appen

Top Subject Matter

Conversational AI and multimodal content evaluation (image + text)

ML/CV dataset labeling and RLHF-based AI response evaluation

Legal Services & Contract Review

Top Data Types

Image

Text

Document

Top Task Types

RLHF

Freelancer Overview

Detail-oriented Freelance AI Training Data Annotator and Remote Data Assistant with a strong background in data labelling, classification, and administration. Proven expertise in following complex guidelines with high precision, managing datasets, and ensuring quality control. Skilled in utilizing office tools and digital platforms effectively to complete tasks efficiently. Education includes Postgraduate Diploma in Education, Lead City University (2025) and Higher National Diploma, The Polytechnic, Ibadan (2019). AI-training focus includes data types such as Image and labeling workflows including Evaluation, Rating, and RLHF.

Labeling Experience

Technical Data Annotator / AI Quality Auditor (Remote)

OtherImage

Provided quality audits and evaluations for conversational AI model responses, emphasizing safety, formatting, and factual accuracy. Performed multimodal work that included image-related conversation analysis and detailed entity tagging for social media content. Reviewed model outputs and related system artifacts to ensure compliance with precision metrics and strict project guidelines. • Ranked and compared model responses side-by-side for training and safety compliance • Conducted entity tagging for social media content platforms (Instagram) • Performed image editing conversation analysis for multimodal evaluation • Verified guideline adherence through QA audits and precision checks

2026 - Present

Freelance AI Data Annotator / Evaluator (Appen & TELUS International, Remote)

AppenImageRLHF

Performed data labeling, segmentation, and curation for advanced machine learning and computer vision datasets with 100% guideline adherence. Used Reinforcement Learning from Human Feedback (RLHF) to evaluate, rate, and rank AI and LLM responses based on factual precision, tone, safety, and constraint compliance. Produced pixel-perfect visual annotations using image rating, object masking, and pattern extraction for model training. • Labeled and segmented data for ML/CV training datasets • Rated and ranked LLM responses using RLHF criteria (factual accuracy, safety, tone) • Performed image rating, object masking, and pattern extraction for visual datasets • Supported global projects (Project Lantana, Project Serene) with top-tier quality benchmarks

2025 - 2026

Education

Work History