Idris Garad

Key Skills

Software

CloudFactory

Data Annotation Tech

Mindrift

OneForma

Remotasks

Scale AI

CVAT

Top Subject Matter

Advanced Transcription Services

Data Labeling and Annotation

Audio Editing and Post-Production

Top Data Types

Audio

Image

Text

Top Task Types

Computer Programming Coding

Prompt Response Writing SFT

Question Answering

Text Summarization

Translation Localization

Freelancer Overview

I have extensive experience in data labeling and AI training data preparation, working across various industries, including tech, media, and research. My expertise lies in accurately labeling and annotating data for machine learning applications, with a strong focus on image and video annotation, natural language processing, and speech recognition. I have contributed to numerous projects that involve the development and refinement of AI models, ensuring that the data provided is of the highest quality. Proficient in a wide range of annotation tools and platforms, I excel in delivering consistent and precise data labeling services. My attention to detail and understanding of complex data labeling protocols have enabled me to work on high-profile projects that demand accuracy and reliability. I am committed to maintaining data integrity and continually improving my skills to meet the evolving needs of AI and machine learning projects. My adaptability and dedication make me a valuable contributor to any project requiring expert data labeling and AI training data preparation.

Labeling Experience

Autonomous Vehicle Data Annotation Specialist

CVATVideoPolygonEntity Ner Classification

This project focused on the annotation of data for autonomous vehicle systems, aiming to improve the accuracy of object detection and recognition models. The scope included labeling tasks such as bounding box annotation for vehicles and pedestrians, semantic segmentation for differentiating road surfaces and environments, polyline annotation for lane markings, and 3D cuboid annotation for objects in LiDAR data. The project handled over 10,000 images and video frames, adhering to rigorous quality standards, including cross-verification and auditing processes to ensure data accuracy. The high-quality annotated data played a crucial role in advancing the company's autonomous driving capabilities.

This project focused on the annotation of data for autonomous vehicle systems, aiming to improve the accuracy of object detection and recognition models. The scope included labeling tasks such as bounding box annotation for vehicles and pedestrians, semantic segmentation for differentiating road surfaces and environments, polyline annotation for lane markings, and 3D cuboid annotation for objects in LiDAR data. The project handled over 10,000 images and video frames, adhering to rigorous quality standards, including cross-verification and auditing processes to ensure data accuracy. The high-quality annotated data played a crucial role in advancing the company's autonomous driving capabilities.

2023 - 2024

Education

Work History