Coin Guru

Key Skills

Software

Labelbox

Scale AI

CVAT

Appen

Top Subject Matter

Autonomous Vehicles

Retail Domain Expertise

Medical Imaging

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Entity Ner Classification

Classification

Text Generation

Text Summarization

Transcription

Evaluation Rating

Object Detection

Polygon

Point Key Point

Freelancer Overview

Object Annotator & Data Labeling Specialist. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Labelbox, Scale AI, and CVAT. Education includes High School Diploma, N/A. AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box, Entity (NER) Classification, and Classification.

Labeling Experience

Object Annotator & Data Labeling Specialist

LabelboxImageBounding Box

As an Object Annotator and Data Labeling Specialist, I performed high-volume image annotation tasks for machine learning model training across domains such as autonomous vehicles, retail, and medical imaging. I applied detailed ontologies using bounding boxes and polygons to accurately identify and classify a wide range of objects. My responsibilities included maintaining quality benchmarks, adhering to strict guidelines, and contributing feedback for process improvement. • Annotated over 10,000 images per month using tools such as Labelbox, Scale AI, and CVAT. • Maintained accuracy rates above 97% based on audit results and inter-annotator agreement. • Collaborated with senior reviewers by flagging ambiguous cases and edge instances. • Provided written feedback that reduced team labeling errors by 18%.

As an Object Annotator and Data Labeling Specialist, I performed high-volume image annotation tasks for machine learning model training across domains such as autonomous vehicles, retail, and medical imaging. I applied detailed ontologies using bounding boxes and polygons to accurately identify and classify a wide range of objects. My responsibilities included maintaining quality benchmarks, adhering to strict guidelines, and contributing feedback for process improvement. • Annotated over 10,000 images per month using tools such as Labelbox, Scale AI, and CVAT. • Maintained accuracy rates above 97% based on audit results and inter-annotator agreement. • Collaborated with senior reviewers by flagging ambiguous cases and edge instances. • Provided written feedback that reduced team labeling errors by 18%.

2022 - Present

Autonomous Vehicle Object Detection Dataset - Annotator & Reviewer

LabelboxImageBounding Box

I was responsible for annotating multi-class bounding boxes for an autonomous vehicle object detection dataset. This entailed labeling images to classify pedestrians, vehicles, traffic signs, and road markings for AI model training. I developed and standardized edge case guidelines and took on a senior reviewer role for final data validation. • Annotated 15,000+ street-level images for self-driving applications. • Achieved a 98.5% quality score on random audits and validations. • Authored guidelines for ambiguous objects to ensure annotation consistency. • Contributed to a team of over 30 annotators on project workflows.

I was responsible for annotating multi-class bounding boxes for an autonomous vehicle object detection dataset. This entailed labeling images to classify pedestrians, vehicles, traffic signs, and road markings for AI model training. I developed and standardized edge case guidelines and took on a senior reviewer role for final data validation. • Annotated 15,000+ street-level images for self-driving applications. • Achieved a 98.5% quality score on random audits and validations. • Authored guidelines for ambiguous objects to ensure annotation consistency. • Contributed to a team of over 30 annotators on project workflows.

2023 - 2024

E-Commerce Product Tagging Initiative - Data Annotator

LabelboxImageClassification

I classified and tagged product images with hierarchical attribute labels for an e-commerce recommendation engine project. This included identifying category, color, material, and style for each item. My efforts reduced misclassification rates and created resources for ongoing annotation accuracy. • Labeled and tagged over 50,000 product images with detailed attributes. • Created a reusable taxonomy sheet that reduced errors by 14%. • Maintained daily throughput of 500+ annotated images while meeting strict quality thresholds. • Worked independently to meet project deadlines and goals.

I classified and tagged product images with hierarchical attribute labels for an e-commerce recommendation engine project. This included identifying category, color, material, and style for each item. My efforts reduced misclassification rates and created resources for ongoing annotation accuracy. • Labeled and tagged over 50,000 product images with detailed attributes. • Created a reusable taxonomy sheet that reduced errors by 14%. • Maintained daily throughput of 500+ annotated images while meeting strict quality thresholds. • Worked independently to meet project deadlines and goals.

2022 - 2023

NLP Sentiment & Intent Labeling - Data Annotator

AppenTextClassification

I labeled customer service chat transcripts with sentiment and intent categories to support conversational AI training. This included classifying data for positive, neutral, and negative sentiment as well as intent identification. My linguistic expertise resolved ambiguous cases, improving model accuracy. • Tagged over 20,000 chat transcripts for sentiment and intent. • Improved model evaluation scores by 10% through accurate labeling. • Ensured clarity and correctness even in complex transcript scenarios. • Supported cleaner training datasets for NLP/AI models.

I labeled customer service chat transcripts with sentiment and intent categories to support conversational AI training. This included classifying data for positive, neutral, and negative sentiment as well as intent identification. My linguistic expertise resolved ambiguous cases, improving model accuracy. • Tagged over 20,000 chat transcripts for sentiment and intent. • Improved model evaluation scores by 10% through accurate labeling. • Ensured clarity and correctness even in complex transcript scenarios. • Supported cleaner training datasets for NLP/AI models.

2021 - 2022

English Content Reviewer & Editor

AppenTextEntity Ner Classification

As an English Content Reviewer and Editor, I managed annotation and review tasks for natural language model training. My work included text classification, sentiment tagging, intent labeling, and named entity recognition on diverse documents. I ensured high standards in grammar, compliance, and consistency for NLP training datasets. • Proofread over 500 documents per month for model development. • Improved dataset content quality scores by 22% through structured feedback reports. • Collaborated on annotation guideline development for distributed teams. • Enhanced consistency and clarity across document-level annotations.

As an English Content Reviewer and Editor, I managed annotation and review tasks for natural language model training. My work included text classification, sentiment tagging, intent labeling, and named entity recognition on diverse documents. I ensured high standards in grammar, compliance, and consistency for NLP training datasets. • Proofread over 500 documents per month for model development. • Improved dataset content quality scores by 22% through structured feedback reports. • Collaborated on annotation guideline development for distributed teams. • Enhanced consistency and clarity across document-level annotations.

2020 - 2022

Education

Work History