Gbeminiyi David

Key Skills

Software

Appen

CrowdSource

Mercor

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Data Collection

Emotion Recognition

Object Detection

Prompt Response Writing SFT

Text Generation

Freelancer Overview

Skilled in data labelling and annotation for machine learning and AI projects, ensuring high-quality and accurate dataset preparation. Experienced with image, text, and audio labelling tasks, maintaining consistency across large data volumes. Proficient in using labelling tools such as Appen, mercor etc. Strong understanding of data taxonomy, classification, and quality control processes. Demonstrated ability to meet strict deadlines while maintaining 99%+ annotation accuracy. Experienced in reviewing and validating labelled data to ensure alignment with project standards and AI training objectives.

Labeling Experience

RWS Diamond & Ruby Projects – AI Content & Image Training Tasks

AppenImageObject DetectionText Summarization

Acting as both prompt user and AI responder: crafting realistic prompts and corresponding AI replies to help model training in various contexts (customer support, casual dialogue, instruction-following, etc.). Performing Entity Recognition (NER) and Sentiment / Emotion Recognition on text inputs to tag key entities (names, dates, product mentions) and emotions (happy, frustrated, neutral). Generating text summarizations and condensed versions of longer texts to assist in multi-turn dialogue training. Executing image personalization tasks: adapting images according to prompt instructions, applying style changes, and making modifications to match textual context. Working on face swap / image manipulation (Ruby tasks) to create aligned, high-fidelity face transfers with natural appearance, respecting identity consistency and ethical boundaries. Performing quality evaluation / rating: reviewing peer output, scoring the correctness, coherence, and adherence to guidelines, and providing

Acting as both prompt user and AI responder: crafting realistic prompts and corresponding AI replies to help model training in various contexts (customer support, casual dialogue, instruction-following, etc.). Performing Entity Recognition (NER) and Sentiment / Emotion Recognition on text inputs to tag key entities (names, dates, product mentions) and emotions (happy, frustrated, neutral). Generating text summarizations and condensed versions of longer texts to assist in multi-turn dialogue training. Executing image personalization tasks: adapting images according to prompt instructions, applying style changes, and making modifications to match textual context. Working on face swap / image manipulation (Ruby tasks) to create aligned, high-fidelity face transfers with natural appearance, respecting identity consistency and ethical boundaries. Performing quality evaluation / rating: reviewing peer output, scoring the correctness, coherence, and adherence to guidelines, and providing

2025 - 2025

Education

Work History