Yahya Mohammed

Key Skills

Software

Data Annotation Tech

Google Cloud Vertex AI

Scale AI

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Image

Top Task Types

Audio Recording

Computer Programming Coding

Prompt Response Writing SFT

RLHF

Tracking

Freelancer Overview

I have hands-on experience in AI training data projects, with a strong focus on data labeling for computer vision and natural language processing tasks. My work has included annotating images and videos for object detection, segmentation, and classification, particularly in domains like autonomous driving and retail analytics. I am also skilled in text-based tasks such as sentiment analysis, entity recognition, and prompt evaluation for large language models (LLMs). I bring consistency, accuracy, and a strong attention to detail to every project I contribute to. What sets me apart is my ability to work efficiently across multiple data modalities—text, image, and video—while maintaining high-quality standards. I’m comfortable using a wide range of annotation tools and following complex labeling guidelines. My bilingual fluency in English and Arabic further enables me to contribute to multilingual projects and cross-cultural datasets with confidence and precision.

Labeling Experience

Street Scene Annotation for Autonomous Driving Dataset

LabelboxComputer Code ProgrammingComputer Programming CodingPrompt Response Writing SFT

I participated in a large-scale data labeling project focused on improving the perception systems of autonomous vehicles. My role involved accurately annotating thousands of frames from dashcam footage with bounding boxes and segmentation masks for objects like pedestrians, vehicles, traffic signs, and lane markings. I followed strict quality guidelines to ensure consistency and precision, and I regularly passed quality audits with a 98%+ accuracy rate. This project enhanced my expertise in computer vision tasks and taught me how to work efficiently with high-resolution data while maintaining accuracy under time constraints.

I participated in a large-scale data labeling project focused on improving the perception systems of autonomous vehicles. My role involved accurately annotating thousands of frames from dashcam footage with bounding boxes and segmentation masks for objects like pedestrians, vehicles, traffic signs, and lane markings. I followed strict quality guidelines to ensure consistency and precision, and I regularly passed quality audits with a 98%+ accuracy rate. This project enhanced my expertise in computer vision tasks and taught me how to work efficiently with high-resolution data while maintaining accuracy under time constraints.

2023 - 2024

Education

Work History