Gabriel Shaba

Key Skills

Software

Other

Mindrift

Appen

Data Annotation Tech

Micro1

Mercor

OneForma

Remotasks

Scale AI

Surge AI

Toloka

Telus

Anno-Mage

Top Subject Matter

AI Model Output Assessment

AI Language Model Training

AI Data Annotator

Top Data Types

Text

Image

Video

Top Task Types

RLHF

Bounding Box

Segmentation

Classification

Entity (NER) Classification

Point/Key Point

Polyline

Cuboid

Object Detection

Text Generation

Question Answering

Text Summarization

Fine-tuning

Polygon

Transcription

Evaluation/Rating

Freelancer Overview

Detail-oriented AI Training Specialist and Quality Analyst with a background in law and professional writing, experienced in improving model reasoning, output accuracy, and policy alignment through structured annotation, QA audits, and linguistic evaluation. Brings a blend of legal precision, analytical rigor, and language expertise to enhance model reliability, reduce hallucinations, and strengthen contextual alignment in AI systems. Skilled in RLHF workflows, prompt evaluation, semantic review, and structured feedback pipelines, with a consistent track record of delivering high-accuracy annotations, improving dataset consistency, and contributing to overall AI system trustworthiness.

Labeling Experience

Artificial Intelligence Researcher (Freelance)

OtherText

Evaluated AI-generated outputs to improve model reasoning and accuracy. Conducted analytical feedback loops and error classification to aid AI model refinement. Assessed outputs for linguistic precision, coherence, and policy compliance. • Structured evaluation for reasoning and contextual accuracy • Provided analytical feedback for model improvement • Reviewed outputs for compliance and risk • Enhanced reliability by flagging hallucinations and biases

Evaluated AI-generated outputs to improve model reasoning and accuracy. Conducted analytical feedback loops and error classification to aid AI model refinement. Assessed outputs for linguistic precision, coherence, and policy compliance. • Structured evaluation for reasoning and contextual accuracy • Provided analytical feedback for model improvement • Reviewed outputs for compliance and risk • Enhanced reliability by flagging hallucinations and biases

2025 - 2026

Data Annotator

MindriftTextRLHF

Annotated and reviewed complex textual datasets following strict procedural guidelines. Evaluated AI responses on helpfulness, honesty, and safety, and performed structured validation. Contributed to semantic review and pattern identification to strengthen dataset consistency. • Labeled text data for AI model training • Performed RLHF tasks and semantic review • Conducted structured validation of datasets • Provided feedback for continual model improvement

Annotated and reviewed complex textual datasets following strict procedural guidelines. Evaluated AI responses on helpfulness, honesty, and safety, and performed structured validation. Contributed to semantic review and pattern identification to strengthen dataset consistency. • Labeled text data for AI model training • Performed RLHF tasks and semantic review • Conducted structured validation of datasets • Provided feedback for continual model improvement

2023 - 2025

Education

Work History