Jatin Lakhorkar

Key Skills

Software

CVAT

Top Subject Matter

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Top Data Types

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Top Label Types

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Freelancer Overview

I am a detail-oriented IT professional with hands-on experience in system setup, user support, and technical troubleshooting within enterprise environments. My background includes managing user accounts, configuring network settings, and working with enterprise software like SAP, which has strengthened my attention to detail and ability to follow complex guidelines—skills essential for high-quality data labeling and annotation work. I am comfortable working with various tools and systems, and my technical foundation enables me to quickly learn new data platforms and annotation processes. I am eager to contribute to AI training data projects where accuracy, consistency, and reliability are critical.

Labeling Experience

Senior Data Annotator & Quality Auditor

CVATImageSegmentation

As a Senior Data Annotator & Quality Auditor, I performed complex image annotation tasks for autonomous vehicle training datasets. I utilized semantic segmentation and bounding box techniques to ensure high accuracy and data quality. My work involved leading quality audits, reducing label noise, and supporting the ML team's data requirements. • Labeled over 5,000 images using CVAT and Labelbox for segmentation and bounding box tasks. • Conducted weekly audits to maintain over 99% accuracy and reduce label noise by 15%. • Identified and addressed edge cases within training data for robust AI model development. • Collaborated with team members to establish standards for annotation tasks.

As a Senior Data Annotator & Quality Auditor, I performed complex image annotation tasks for autonomous vehicle training datasets. I utilized semantic segmentation and bounding box techniques to ensure high accuracy and data quality. My work involved leading quality audits, reducing label noise, and supporting the ML team's data requirements. • Labeled over 5,000 images using CVAT and Labelbox for segmentation and bounding box tasks. • Conducted weekly audits to maintain over 99% accuracy and reduce label noise by 15%. • Identified and addressed edge cases within training data for robust AI model development. • Collaborated with team members to establish standards for annotation tasks.

2024 - 2024

Education

Work History