Rima Al Rashid

Key Skills

Software

Other

Appen

Top Subject Matter

Large Language Models (LLMs) / AI Model Evaluation

Automatic Speech Recognition (ASR) / Caption Generation

image and video

Top Data Types

Text

Audio

Document

Top Task Types

Transcription

Freelancer Overview

AI Data Annotator & Evaluator. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Appen. Education includes Master of Business Administration, University of Petra (2019) and Bachelor of Computer Science, University of Petra (2015). AI-training focus includes data types such as Text and Audio and labeling workflows including Evaluation, Rating, and Transcription.

Labeling Experience

AI Data Annotator & Evaluator

OtherTextEvaluation Rating

Evaluated and annotated outputs from large language models (LLMs) in multiple tasks to optimize AI system performance. Used predefined guidelines to assess accuracy, completeness, and quality of generated text responses. Handled both subjective and objective evaluation methods to enhance annotation reliability. • Conducted intent analysis, supervised fine-tuning (SFT), reward model ranking, and scoring. • Performed double-blind evaluations and ensured high annotation standards. • Provided feedback on model errors and improvement opportunities. • Contributed to auto-evaluation dataset creation and handled multilingual annotation tasks.

Evaluated and annotated outputs from large language models (LLMs) in multiple tasks to optimize AI system performance. Used predefined guidelines to assess accuracy, completeness, and quality of generated text responses. Handled both subjective and objective evaluation methods to enhance annotation reliability. • Conducted intent analysis, supervised fine-tuning (SFT), reward model ranking, and scoring. • Performed double-blind evaluations and ensured high annotation standards. • Provided feedback on model errors and improvement opportunities. • Contributed to auto-evaluation dataset creation and handled multilingual annotation tasks.

2026 - 2026

Data Annotator & Transcription

AppenAudioTranscription

Annotated and transcribed Arabic audio data to support automatic speech recognition and caption generation systems. Labeled audio files with high accuracy, capturing linguistic nuances, slang, and dialect-specific features. Validated and improved model performance for multilingual and dialect-rich environments. • Recognized dialect variations for Jordanian and regional Arabic. • Ensured transcription accuracy per detailed guidelines. • Improved AI-generated captions through precise labeling. • Maintained strict adherence to annotation standards.

Annotated and transcribed Arabic audio data to support automatic speech recognition and caption generation systems. Labeled audio files with high accuracy, capturing linguistic nuances, slang, and dialect-specific features. Validated and improved model performance for multilingual and dialect-rich environments. • Recognized dialect variations for Jordanian and regional Arabic. • Ensured transcription accuracy per detailed guidelines. • Improved AI-generated captions through precise labeling. • Maintained strict adherence to annotation standards.

2022 - 2022

Education

Work History