Mahmud Musa

Key Skills

Software

Scale AI

Telus

Appen

Other

Top Subject Matter

Financial Compliance & Risk Analysis

Business Writing

Technology Policy & Product Operations

Top Data Types

Text

Document

Image

Top Task Types

RLHF

Entity Ner Classification

Segmentation

Bounding Box

Freelancer Overview

Senior AI Trainer & RLHF Specialist. Brings 2+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Scale AI, Telus, and Appen. Education includes Bachelor of Science, Bayero University Kano (2025). AI-training focus includes data types such as Text, Document, and Image and labeling workflows including RLHF, Entity (NER) Classification, and Segmentation.

Labeling Experience

Senior AI Trainer & RLHF Specialist

Scale AITextRLHF

As a Senior AI Trainer and RLHF Specialist at Outlier AI (Scale AI Partner), I evaluated and ranked LLM model outputs for usefulness, accuracy, and safety. I created high-quality preference rankings and conducted red-teaming to uncover model vulnerabilities. My labeling work supported reward model pipelines and contributed to measurable model improvements. • Ranked LLM responses using RLHF for finance, business, and technology prompts. • Delivered consistent, high-quality preference annotation across 2,000+ tasks. • Performed red-teaming to surface hallucinations and policy violations. • Maintained above 95% quality score across all assignments.

As a Senior AI Trainer and RLHF Specialist at Outlier AI (Scale AI Partner), I evaluated and ranked LLM model outputs for usefulness, accuracy, and safety. I created high-quality preference rankings and conducted red-teaming to uncover model vulnerabilities. My labeling work supported reward model pipelines and contributed to measurable model improvements. • Ranked LLM responses using RLHF for finance, business, and technology prompts. • Delivered consistent, high-quality preference annotation across 2,000+ tasks. • Performed red-teaming to surface hallucinations and policy violations. • Maintained above 95% quality score across all assignments.

2023 - Present

AI Data Annotator — Finance & Code Domains

TelusDocumentEntity Ner Classification

As an AI Data Annotator at Telus International, I annotated financial documents and business texts to train NLP models. My primary activities involved entity recognition, sentiment analysis, and intent classification on multilingual data. Collaboration with QA leads ensured high annotation quality and project standards. • Annotated earnings reports, correspondence, and business documents. • Applied NER, sentiment, and intent labels across datasets. • Completed 1,500+ tasks with a 97% accuracy rating. • Improved inter-annotator agreement through QA feedback.

As an AI Data Annotator at Telus International, I annotated financial documents and business texts to train NLP models. My primary activities involved entity recognition, sentiment analysis, and intent classification on multilingual data. Collaboration with QA leads ensured high annotation quality and project standards. • Annotated earnings reports, correspondence, and business documents. • Applied NER, sentiment, and intent labels across datasets. • Completed 1,500+ tasks with a 97% accuracy rating. • Improved inter-annotator agreement through QA feedback.

2022 - 2022

AI Annotation Contributor

OtherImageBounding Box

While contributing to AI annotation projects at Crowdgen and Atlas Capture, I completed tasks in bounding box annotation, segmentation, and text span tagging. My responsibilities also included verifying AI-generated content for accuracy, particularly in finance. This experience involved cross-platform annotation and maintaining performance across multiple environments. • Labeled images using bounding box and segmentation techniques. • Verified AI-generated financial data for correctness. • Demonstrated expertise in financial content annotation. • Built a cross-platform annotation portfolio.

While contributing to AI annotation projects at Crowdgen and Atlas Capture, I completed tasks in bounding box annotation, segmentation, and text span tagging. My responsibilities also included verifying AI-generated content for accuracy, particularly in finance. This experience involved cross-platform annotation and maintaining performance across multiple environments. • Labeled images using bounding box and segmentation techniques. • Verified AI-generated financial data for correctness. • Demonstrated expertise in financial content annotation. • Built a cross-platform annotation portfolio.

2021 - 2022

Data Collection & Annotation Specialist

AppenImageSegmentation

At Appen, I collected and labeled data for image recognition, audio transcription, and search relevance tasks. I performed segmentation and applied annotation guidelines to maintain labeling consistency. My work contributed to foundational datasets for machine learning projects. • Labeled structured image datasets and performed audio transcriptions. • Annotated web results for search relevance and user intent alignment. • Ensured consistent application of annotation standards. • Participated in high-volume labeling batches for diverse AI use cases.

At Appen, I collected and labeled data for image recognition, audio transcription, and search relevance tasks. I performed segmentation and applied annotation guidelines to maintain labeling consistency. My work contributed to foundational datasets for machine learning projects. • Labeled structured image datasets and performed audio transcriptions. • Annotated web results for search relevance and user intent alignment. • Ensured consistent application of annotation standards. • Participated in high-volume labeling batches for diverse AI use cases.

2021 - 2022

Education

Work History