Ibrahim Raymond

Key Skills

Software

Scale AI

Data Annotation Tech

Other

Top Subject Matter

AI-generated Text Evaluation and Annotation

AI Response Evaluation and Red Teaming

Freelance AI Content Review and Moderation

Top Data Types

Text

Image

Document

Top Task Types

Data Collection

Transcription

Text Generation

Segmentation

Bounding Box

Evaluation/Rating

Freelancer Overview

AI Content Evaluator / Data Annotator. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Scale AI, Data Annotation Tech, and Other. Education includes Bachelor of Science, Elizade University (2022). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

Freelance AI Content Reviewer / Research Writer

OtherText

Reviewed AI-generated and human-authored content for accuracy, clarity, and compliance in freelance client engagements. Ensured outputs met editorial standards by identifying and rewriting or flagging weak, misleading, or policy-conflicting submissions. Applied structured moderation and comprehensive literature reviews for content quality assurance. • Maintained high client satisfaction and strong repeat business through quality delivery. • Synthesized complex material into accessible, well-organized summaries per guidelines. • Managed multiple annotation and moderation projects concurrently. • Focused on content relevant to AI, technology, and associated domains.

Reviewed AI-generated and human-authored content for accuracy, clarity, and compliance in freelance client engagements. Ensured outputs met editorial standards by identifying and rewriting or flagging weak, misleading, or policy-conflicting submissions. Applied structured moderation and comprehensive literature reviews for content quality assurance. • Maintained high client satisfaction and strong repeat business through quality delivery. • Synthesized complex material into accessible, well-organized summaries per guidelines. • Managed multiple annotation and moderation projects concurrently. • Focused on content relevant to AI, technology, and associated domains.

2024 - Present

AI Trainer / Response Reviewer

Data Annotation TechText

Reviewed, ranked, and evaluated over 5,000 AI responses across text and image modalities with DataAnnotation.tech. Used binary, 5-point, and pairwise rubrics to identify hallucinations, safety violations, and instruction drift. Employed red teaming and adversarial prompt evaluation to surface model weaknesses and drive improvements. • Audited model outputs for factuality, usefulness, safety, and guideline compliance. • Worked within calibration-focused, rubric-based QA workflows to ensure consistency. • Utilized Label Studio, Google Sheets, and internal platforms for efficient tracking and submission. • Prioritized quality control and rigorous standardization in all audits and evaluations.

Reviewed, ranked, and evaluated over 5,000 AI responses across text and image modalities with DataAnnotation.tech. Used binary, 5-point, and pairwise rubrics to identify hallucinations, safety violations, and instruction drift. Employed red teaming and adversarial prompt evaluation to surface model weaknesses and drive improvements. • Audited model outputs for factuality, usefulness, safety, and guideline compliance. • Worked within calibration-focused, rubric-based QA workflows to ensure consistency. • Utilized Label Studio, Google Sheets, and internal platforms for efficient tracking and submission. • Prioritized quality control and rigorous standardization in all audits and evaluations.

2023 - Present

AI Content Evaluator / Data Annotator

Scale AIText

Evaluated AI-generated text responses for quality, grammar, clarity, and adherence to guidelines on Scale AI's platform. Performed pairwise response ranking, prompt evaluation, and detailed rubric-based feedback for safety, helpfulness, and instruction-following. Maintained high annotation throughput and consistent accuracy across large-volume datasets. • Conducted named entity recognition (NER), intent classification, sentiment tagging, and taxonomy labeling on text data. • Completed 150–200 annotation and evaluation tasks per week with a 95%+ quality score. • Adapted swiftly to guideline updates to maintain output standards. • Contributed feedback on hallucinations, unsupported claims, and policy violations for model improvement.

Evaluated AI-generated text responses for quality, grammar, clarity, and adherence to guidelines on Scale AI's platform. Performed pairwise response ranking, prompt evaluation, and detailed rubric-based feedback for safety, helpfulness, and instruction-following. Maintained high annotation throughput and consistent accuracy across large-volume datasets. • Conducted named entity recognition (NER), intent classification, sentiment tagging, and taxonomy labeling on text data. • Completed 150–200 annotation and evaluation tasks per week with a 95%+ quality score. • Adapted swiftly to guideline updates to maintain output standards. • Contributed feedback on hallucinations, unsupported claims, and policy violations for model improvement.

2023 - Present

Education

Work History