Abdulkareem F.

Key Skills

Software

Anno-Mage

Appen

Axiom AI

Clickworker

Data Annotation Tech

HiveMind

Remotasks

CrowdSource

CrowdFlower

CVAT

Dataloop

Datatroniq

Datumbox

Datasaur

Labelbox

Kili Technology

LabelImg

Label Studio

LightTag

Lionbridge

Mercor

Mighty AI

AWS SageMaker

Encord

Doccano

Diffgram

OneForma

OpenCV AI Kit (OAK)

Playment

Prodigy

V7 Labs

Trilldata Technologies

VoTT

Scale AI

Sama

Sloth

Roboflow

Redbrick AI

Mindrift

Micro1

Datature

Google Cloud Vertex AI

Deep Systems

Dataturk

Supervisely

SuperAnnotate

Snorkel AI

Don't disclose

Other

Top Subject Matter

Computer Vision

Speech and Audio Processing

Top Data Types

Audio

Computer Code Programming

Document

Image

Medical Dicom

Text

Video

Top Task Types

Action Recognition

Audio Recording

Bounding Box

Classification

Computer Programming/Coding

Data Collection

Emotion Recognition

Entity (NER) Classification

Evaluation/Rating

Fine-tuning

Function Calling

Land Cover Classification

Mapping

Object Detection

Prompt + Response Writing (SFT)

Question Answering

Red Teaming

Relationship

RLHF

Routing

Segmentation

Text Generation

Text Summarization

Tracking

Transcription

Translation/Localization

Polygon

Freelancer Overview

AI Data Annotation Specialist (Text labeling) — Appen Remote, United States. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Appen, OneForma, and Other. Education includes Bachelor of Science, University of the People and National Diploma, Federal Polytechnic Bida (2023). AI-training focus includes data types such as Text, Video, and Image and labeling workflows including Entity (NER), Evaluation, and Rating.

Labeling Experience

Freelance Annotation Specialist (Appen, CrowdGen, Atlas AI)

AppenTextEntity (NER) Classification

Annotated and labeled diverse datasets including text, image, and audio data for machine learning and LLM training. Focused on natural language understanding, sentiment analysis, bounding boxes, semantic segmentation, and entity recognition. Consistently maintained 99%+ quality scores across 50+ projects, improving model accuracy and data pipeline efficiency. • Delivered rapid and precise work with 99% accuracy. • Specialized in NLP and computer vision labeling tasks. • Utilized platforms such as Appen, CrowdGen, and Atlas AI. • Ensured high standards in data integrity and annotation consistency.

2019 - 2020

Freelance Specialist (Video Segmentation)

OtherImageSegmentationBounding Box

Performed frame-by-frame video segmentation, object tracking, and scene labeling for advanced computer vision models. Applied polygon, bounding box, and semantic masks across multi-frame datasets to ensure spatial and temporal consistency. Collaborated with QA reviewers to resolve edge cases in motion tracking while optimizing annotation speed without sacrificing pixel-level accuracy. • Performed temporal video segmentation and object tracking • Applied polygon, bounding box, and semantic masks across multi-frame datasets • Ensured consistency across frames to prevent model drift • Optimized annotation speed while preserving pixel-level accuracy

2024 - Present

QA Expert — Mercor AI United States (Remote)

MercorText

Performed QA reviews of AI training or annotation-related outputs to ensure quality and consistency. Conducted ongoing evaluations while following established quality criteria. Supported continuous improvement by verifying that outputs meet required standards. • Checked outputs against predefined QA criteria • Maintained consistent evaluation quality over repeated tasks • Supported process adherence and reporting • Contributed to higher reliability of AI training data and outputs

2023 - Present

AI Trainer (LLM and mixed annotation auditing) — OneForma/Centific Remote

OneFormaText

Performed prompt and model-output review for LLM training and conversational quality checks. Completed auditing, search relevance evaluation, and prompt review as part of mixed annotation generalist workloads. Evaluated NLP and computer vision workstreams while maintaining label quality and reliability standards. • Reviewed prompts and conversational flows for training readiness • Conducted mixed workloads including auditing and search relevance evaluation • Ensured labeling consistency across cross-functional tasks • Identified issues affecting downstream model performance and relevance

2023 - Present

AI Generalist (Cross-Functional) - OneForma

AppenImageBounding BoxPolygon

You supported multiple AI initiatives across NLP, computer vision, and speech projects as a cross-functional generalist. You adapted to changing annotation schemas and evolving model objectives while maintaining strong performance. You contributed to pilot programs and scaling efforts during high-volume production cycles through careful task execution and quality awareness. • Labeled, audited, and reviewed work products including prompt review and search relevance checks • Worked across NLP, CV, and speech-related workflows and task types • Maintained high performance metrics across diverse job requirements • Supported pilot launches and scaling efforts during production cycles

2023 - Present

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Education

Work History