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M

Mercedez Guerrero

Operations Coordinator

USA flag
N/A, Usa
$30.00/hrEntry LevelLabelboxCrowdsourceCVAT

Key Skills

Software

LabelboxLabelbox
CrowdSourceCrowdSource
CVATCVAT

Top Subject Matter

Artificial Intelligence & Machine Learning
Computer Vision (Image Annotation)
Construction / Real-World Environment Data

Top Data Types

DocumentDocument
ImageImage
TextText

Top Task Types

Segmentation
Classification
Text Generation
Text Summarization
Object Detection
Question Answering
Transcription
Evaluation Rating
Data Collection
Function Calling

Freelancer Overview

I have hands-on experience in data labeling and AI training support, with a strong focus on image annotation, segmentation, and text classification. I have worked on projects involving object detection, equipment labeling, and structural element annotation, as well as customer inquiry classification for NLP tasks. My work emphasizes accuracy, consistency, and adherence to detailed labeling guidelines, along with performing quality assurance reviews to ensure high-quality datasets for machine learning models. What sets me apart is my real-world construction and operations background, which allows me to bring deeper context and precision when working with visual and structured data. I am highly detail-oriented, efficient with large datasets, and comfortable handling complex labeling tasks, including edge cases and ambiguous data. I combine practical field knowledge with strong organizational skills to deliver reliable, high-quality annotation work that directly supports model performance.

Entry LevelEnglish

Labeling Experience

Image Annotation

ImageSegmentation
Annotated construction site images for machine learning models focused on object detection and site safety. Tasks included segmentation of equipment, workers, materials, and structural elements (footings, walls, slabs). Maintained high accuracy by following detailed labeling guidelines and performing quality checks. Experience leveraged real-world construction knowledge to improve labeling precision and context awareness.

Annotated construction site images for machine learning models focused on object detection and site safety. Tasks included segmentation of equipment, workers, materials, and structural elements (footings, walls, slabs). Maintained high accuracy by following detailed labeling guidelines and performing quality checks. Experience leveraged real-world construction knowledge to improve labeling precision and context awareness.

2026 - Present

Blueprint and Structural Element Annotation

ImageClassification
Annotated structural drawings and plan images to identify key elements such as footings, walls, slabs, and rebar layouts. Applied real-world construction experience to ensure accurate interpretation of plans. Supported dataset creation for models focused on plan recognition and automated takeoff systems

Annotated structural drawings and plan images to identify key elements such as footings, walls, slabs, and rebar layouts. Applied real-world construction experience to ensure accurate interpretation of plans. Supported dataset creation for models focused on plan recognition and automated takeoff systems

2023 - Present

Customer Inquiry Text Classification

TextClassification
Performed text labeling on customer inquiries to classify intent (quotes, complaints, scheduling, general questions). Applied consistent tagging rules and reviewed ambiguous cases to maintain dataset integrity. Helped improve automated response systems and routing accuracy.

Performed text labeling on customer inquiries to classify intent (quotes, complaints, scheduling, general questions). Applied consistent tagging rules and reviewed ambiguous cases to maintain dataset integrity. Helped improve automated response systems and routing accuracy.

2020 - Present

Data Annotation Quality Assurance

TextQuestion Answering
Reviewed labeled datasets for accuracy, consistency, and adherence to project guidelines. Identified errors, corrected mislabels, and provided feedback to improve annotation quality. Maintained high-quality standards across datasets used for machine learning training

Reviewed labeled datasets for accuracy, consistency, and adherence to project guidelines. Identified errors, corrected mislabels, and provided feedback to improve annotation quality. Maintained high-quality standards across datasets used for machine learning training

2026 - 2026

Education

I

ISU

N/A, Generals

N/A
2012 - 2014

Work History

J

Jack Guerrero Concrete LLC

Operations Coordinator

N/A
2020 - Present