Augusta Anurika Uwakwe

Key Skills

Software

Appen

iMerit

Lionbridge

Mercor

Mindrift

OneForma

SuperAnnotate

Surge AI

Toloka

Telus

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Computer Code Programming

Document

Geospatial Tiled Imagery

Image

Text

Top Label Types

Action Recognition

Audio Recording

Bounding Box

Classification

Computer Programming Coding

Cuboid

Data Collection

Emotion Recognition

Entity Ner Classification

Evaluation Rating

Object Detection

Point Key Point

Question Answering

RLHF

Segmentation

Text Generation

Text Summarization

Tracking

Transcription

Translation Localization

Freelancer Overview

I am an AI Data Annotation Specialist with over 5 years of experience working on diverse projects involving text, image, and video datasets for NLP and LLM applications. My background in Computer Science and Computational Linguistics allows me to deliver precise annotations, quality assurance, and effective dataset curation. I am highly skilled in using Python and SQL for data cleaning, preprocessing, automation, and large-scale data querying. My work has included collaborating with large language models, prompt engineering, fact-checking AI outputs, and refining annotation workflows. I am detail-oriented, reliable, and adept at following complex guidelines to ensure dataset integrity and accuracy in high-impact AI projects.

Labeling Experience

Data Annotation Specialist / Remote

Don T DiscloseImageBounding BoxPoint Key Point

Working on diverse AI and NLP projects involving text, image, and video datasets. My key responsibilities included: - Annotating and labeling text for sentiment analysis, classification, and summarization tasks. - Performing object detection and action recognition on video datasets to support computer vision models. - Applying emotion and sentiment labeling to improve AI understanding of human communication. - Leveraging Python and SQL for dataset preprocessing, querying, and quality checks. - Following detailed annotation guidelines and QA protocols to ensure high accuracy across multimodal datasets. - Collaborating with team leads to refine workflows, improve labeling consistency, and optimize project efficiency. The project encompassed large-scale multimodal datasets, requiring high attention to detail, consistency, and adherence to strict project standards.

Working on diverse AI and NLP projects involving text, image, and video datasets. My key responsibilities included: - Annotating and labeling text for sentiment analysis, classification, and summarization tasks. - Performing object detection and action recognition on video datasets to support computer vision models. - Applying emotion and sentiment labeling to improve AI understanding of human communication. - Leveraging Python and SQL for dataset preprocessing, querying, and quality checks. - Following detailed annotation guidelines and QA protocols to ensure high accuracy across multimodal datasets. - Collaborating with team leads to refine workflows, improve labeling consistency, and optimize project efficiency. The project encompassed large-scale multimodal datasets, requiring high attention to detail, consistency, and adherence to strict project standards.

2025

AI Annotation / LLM Support / Remote

OneformaTextEntity Ner ClassificationSegmentation

I collaborated on large-scale AI and NLP projects, supporting LLMs through data annotation and prompt refinement. My responsibilities included: Labeling and classifying text data for AI model training across multiple domains. Performing Named Entity Recognition (NER) and text summarization to improve model understanding. Conducting question-answering and text generation tasks to evaluate and enhance LLM outputs. Cleaning, preprocessing, and validating datasets using Python and SQL to ensure accuracy and consistency. Following strict guidelines and quality assurance protocols to maintain dataset integrity. Collaborating with AI systems to refine outputs and improve annotation efficiency. The project involved handling tens of thousands of text entries, ensuring high-quality labeling standards, and contributing to the creation of reliable, high-performing AI models.

I collaborated on large-scale AI and NLP projects, supporting LLMs through data annotation and prompt refinement. My responsibilities included: Labeling and classifying text data for AI model training across multiple domains. Performing Named Entity Recognition (NER) and text summarization to improve model understanding. Conducting question-answering and text generation tasks to evaluate and enhance LLM outputs. Cleaning, preprocessing, and validating datasets using Python and SQL to ensure accuracy and consistency. Following strict guidelines and quality assurance protocols to maintain dataset integrity. Collaborating with AI systems to refine outputs and improve annotation efficiency. The project involved handling tens of thousands of text entries, ensuring high-quality labeling standards, and contributing to the creation of reliable, high-performing AI models.

2024 - 2025

Education

Work History