Lucky Mmadu

Key Skills

Software

Other

CVAT

Label Studio

Micro1

Top Subject Matter

General AI/NLP

Human Activity Recognition

General Computer Vision

Top Data Types

Text

Image

Video

Top Task Types

RLHF

Action Recognition

Bounding Box

Entity (NER) Classification

Freelancer Overview

AI Data Evaluator (RLHF) | Apple Project (via Vendor). Core strengths include Other, CVAT, and Label Studio. Education includes Bachelor of Engineering, Federal University of Technology, Owerri. AI-training focus includes data types such as Text and Image and labeling workflows including RLHF, Action Recognition, and Bounding Box.

Labeling Experience

AI Data Annotator / Quality Reviewer | Atlas Capture

OtherImageAction Recognition

As an AI Data Annotator and Quality Reviewer at Atlas Capture, I checked and revised AI-generated observations about human hand activities in images. My main responsibilities included ensuring correctness and consistency of image annotations in action recognition datasets. I provided annotated data critical for training AI systems to accurately recognize complex human actions. • Reviewed and corrected image labels and descriptions • Ensured coherence and adherence to annotation rules • Delivered datasets for training and validation in action recognition • Fixed errors and raised quality standards for AI model input

As an AI Data Annotator and Quality Reviewer at Atlas Capture, I checked and revised AI-generated observations about human hand activities in images. My main responsibilities included ensuring correctness and consistency of image annotations in action recognition datasets. I provided annotated data critical for training AI systems to accurately recognize complex human actions. • Reviewed and corrected image labels and descriptions • Ensured coherence and adherence to annotation rules • Delivered datasets for training and validation in action recognition • Fixed errors and raised quality standards for AI model input

2025 - 2026

AI Data Evaluator (RLHF) | Apple Project (via Vendor)

OtherTextRLHF

As an AI Data Evaluator for the Apple Project, I compared AI-generated answers using side-by-side assessment for reinforcement learning from human feedback. I applied rubric methodology focused on instruction adherence, accuracy, usefulness, and tone in evaluating text outputs. My evaluations delivered actionable feedback that directly improved AI model alignment and quality. • Compared AI responses via SxS method and provided detailed written explanations • Assessed text data for accuracy, usefulness, and logical coherence • Identified errors in facts, logic, and tone in model outputs • Helped refine RLHF pipelines through comprehensive feedback

As an AI Data Evaluator for the Apple Project, I compared AI-generated answers using side-by-side assessment for reinforcement learning from human feedback. I applied rubric methodology focused on instruction adherence, accuracy, usefulness, and tone in evaluating text outputs. My evaluations delivered actionable feedback that directly improved AI model alignment and quality. • Compared AI responses via SxS method and provided detailed written explanations • Assessed text data for accuracy, usefulness, and logical coherence • Identified errors in facts, logic, and tone in model outputs • Helped refine RLHF pipelines through comprehensive feedback

2024 - 2026

AI Annotation Practice Projects (Self-directed): NER & Text Annotation

Label StudioTextEntity Ner Classification

In my annotation practice projects, I performed Named Entity Recognition and text annotation on various textual datasets. This involved identifying and labeling named entities and other structures within data for NLP applications. My efforts contributed to the preparation of rich, quality-labeled datasets for machine learning. • Completed NER labeling tasks on diverse textual content • Practiced text annotation and entity extraction • Developed annotation guidelines for consistent labeling • Utilized multiple open-source tools for annotation exercises

In my annotation practice projects, I performed Named Entity Recognition and text annotation on various textual datasets. This involved identifying and labeling named entities and other structures within data for NLP applications. My efforts contributed to the preparation of rich, quality-labeled datasets for machine learning. • Completed NER labeling tasks on diverse textual content • Practiced text annotation and entity extraction • Developed annotation guidelines for consistent labeling • Utilized multiple open-source tools for annotation exercises

2024 - 2025

AI Annotation Practice Projects (Self-directed)

CVATImageBounding Box

In self-directed AI annotation practice projects, I conducted image labeling using platforms like CVAT and Label Studio. My work included bounding box annotation, segmentation, and image classification on diverse datasets. I also developed and documented my own annotation guidelines for improved accuracy. • Completed image and segmentation tasks using CVAT and Label Studio • Performed bounding box annotation and image classification • Developed and applied custom annotation protocols • Gained experience with leading annotation tools through hands-on projects

In self-directed AI annotation practice projects, I conducted image labeling using platforms like CVAT and Label Studio. My work included bounding box annotation, segmentation, and image classification on diverse datasets. I also developed and documented my own annotation guidelines for improved accuracy. • Completed image and segmentation tasks using CVAT and Label Studio • Performed bounding box annotation and image classification • Developed and applied custom annotation protocols • Gained experience with leading annotation tools through hands-on projects

Not specified

Education

Work History