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Key Skills

Software

Labelbox

Prodigy

Scale AI

Appen

CVAT

Supervisely

Top Subject Matter

Nlp Domain Expertise

Llms Domain Expertise

AI Safety

Top Data Types

Text

Image

Document

Top Task Types

Entity (NER) Classification

Bounding Box

Freelancer Overview

Expert Data Annotator & AI Data Quality Specialist. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, Prodigy, and Scale AI. Education includes Bachelor of Technology, Jawaharlal Nehru Technological University. AI-training focus includes data types such as Text and Image and labeling workflows including Entity (NER) Classification and Bounding Box.

Labeling Experience

Expert Data Annotator & AI Data Quality Specialist

LabelboxTextEntity (NER) Classification

As an expert data annotator, I annotated and evaluated 50,000+ text samples for NLP and LLM model training. My responsibilities included intent classification, sentiment analysis, NER tagging, and safety labeling, along with hallucination detection and response ranking for large language model outputs. I reviewed annotations for consistency and developed edge-case documentation to improve guidelines. • Conducted bias/misinformation identification and high-risk content escalation. • Increased annotation consistency and reduced hallucination rates with feedback labeling. • Built a gold-standard dataset of 5,000 samples for quality assurance. • Measured inter-annotator agreement and led dataset review initiatives.

2025 - Present

Data Annotator

LabelboxTextEntity (NER) Classification

As a Data Annotator, I labeled customer support and conversational datasets for AI chatbot training. My tasks covered multi-intent and slot filling, named entity recognition, and toxicity/harmful content detection. I worked with annotation guidelines to achieve high accuracy and supported peer review for quality control. • Tagged entities like PERSON, ORG, DATE, MONEY, and PRODUCT. • Completed 30,000+ high-quality annotation tasks and improved chatbot accuracy by 15%. • Operated on daily annotation targets, consistently ensuring >95% accuracy. • Contributed as a peer reviewer to maintain annotation quality.

2023 - 2025

QA Automation Tester (Data Annotation)

CVATImageBounding Box

While at GE as a QA Automation Tester, I annotated retail product images for object detection and classification. Tasks included bounding boxes, polygon segmentation, attribute tagging, and semantic segmentation across multiple product categories. I created validation datasets, resolved annotation conflicts, and implemented quality audits using established tools. • Labeled over 120,000 images, building gold-standard datasets and achieving 99%+ accuracy. • Used annotation tools like CVAT, Labelbox, and Supervisely, and supported model training (YOLO/Faster R-CNN). • Handled edge cases, partial object detection, and defect labeling for model improvement. • Measured annotation agreement and reduced false positives in production models.

Not specified

Education

Work History