Mohamed Ahmed

Key Skills

Software

Scale AI

Other

Top Subject Matter

No subject matter listed

Top Data Types

Text

Image

Top Label Types

Classification

Text Summarization

RLHF

Evaluation Rating

Prompt Response Writing SFT

Segmentation

Transcription

Freelancer Overview

I have over 10 years of experience specializing in technical content review, data labeling, and research analysis, with a strong focus on STEM domains. My background includes reviewing and annotating AI-generated content, performing detailed quality checks, and creating structured Q&A and problem-solving exercises for data science, engineering, and mathematics projects. I am highly skilled in deep reading, fact-checking, and synthesizing complex information to ensure high-quality training data for machine learning applications. My technical toolkit includes Python, MATLAB, R, and leading AI content tools such as ChatGPT and Outlier.ai. I excel at remote, asynchronous collaboration and consistently deliver clear, concise outputs that support robust AI model development.

Labeling Experience

Multimodal AI Training & Annotation (Audio, Image, Video, Text)

OtherImageSegmentationClassification

Currently contributing to multimodal AI training projects involving annotation and evaluation of audio, image, video, and text datasets. Tasks include speech transcription and quality review, image and video object detection/segmentation, multimodal content classification, and evaluation of AI-generated outputs across modalities. Also perform prompt–response authoring and rating for generative and conversational AI systems (RLHF/SFT workflows). Work spans diverse domains including everyday scenes, human activities, speech samples, and multimodal reasoning tasks. Maintain high annotation accuracy through guideline adherence, calibration rounds, and peer review to support robust model training and evaluation.

Currently contributing to multimodal AI training projects involving annotation and evaluation of audio, image, video, and text datasets. Tasks include speech transcription and quality review, image and video object detection/segmentation, multimodal content classification, and evaluation of AI-generated outputs across modalities. Also perform prompt–response authoring and rating for generative and conversational AI systems (RLHF/SFT workflows). Work spans diverse domains including everyday scenes, human activities, speech samples, and multimodal reasoning tasks. Maintain high annotation accuracy through guideline adherence, calibration rounds, and peer review to support robust model training and evaluation.

2025

STEM & LLM Content Annotation and Evaluation

Scale AITextClassificationText Summarization

Worked on large-scale text annotation and evaluation projects for machine learning and LLM training in STEM domains. Tasks included labeling and classifying technical passages, rating AI-generated responses for accuracy and clarity, creating gold-standard summaries and Q&A pairs, and providing structured feedback for model improvement (RLHF). Annotated thousands of STEM items spanning mathematics, data science, and engineering topics. Applied strict quality guidelines, multi-pass review, and consistency checks to ensure high inter-annotator agreement and factual correctness. Collaborated asynchronously with global reviewers and project leads to maintain dataset integrity and annotation standards.

Worked on large-scale text annotation and evaluation projects for machine learning and LLM training in STEM domains. Tasks included labeling and classifying technical passages, rating AI-generated responses for accuracy and clarity, creating gold-standard summaries and Q&A pairs, and providing structured feedback for model improvement (RLHF). Annotated thousands of STEM items spanning mathematics, data science, and engineering topics. Applied strict quality guidelines, multi-pass review, and consistency checks to ensure high inter-annotator agreement and factual correctness. Collaborated asynchronously with global reviewers and project leads to maintain dataset integrity and annotation standards.

2017 - 2023

Education

Work History