Rashmani Kumari

Key Skills

Software

AWS SageMaker

Appen

Clickworker

CrowdSource

Data Annotation Tech

Labelbox

Label Studio

Remotasks

Scale AI

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Classification

Data Collection

Evaluation Rating

Object Detection

Prompt Response Writing SFT

Freelancer Overview

I possess extensive experience in the creation and evaluation of AI training data, focusing on text, image, and video labeling for generative AI initiatives. My responsibilities have included content annotation, quality evaluation and data classification across multilingual datasets, with a particular emphasis on English and Hindi. I have participated in projects related to natural language comprehension, object detection and fine-tuning AI models—ensuring a high degree of data accuracy and consistency. Additionally, I have worked on evaluation and rater projects where I reviewed AI-generated outputs, translations and search relevancy to enhance model quality and user satisfaction. I am proficient in adhering to intricate guidelines and utilizing platforms such as Data Compute, RaterHub and proprietary labeling tools. My experience in managing linguistic subtleties within Hindi-English datasets provides me with a significant advantage in generating trustworthy and high-quality training data for sophisticated AI systems.

Labeling Experience

AI Data Labeling and Evaluation Projects

AppenImageText GenerationEmotion Recognition

Worked on multiple AI training data projects involving text, image and video annotation. Tasks included content classification, translation validation, emotion and intent labeling, bounding box tagging and AI response evaluation. Participated in Hindi-English text evaluation and search relevance rating to improve model accuracy. Contributed to fine-tuning and SFT (Supervised Fine-Tuning) datasets for large language models. Ensured over 98% quality accuracy, consistently adhering to project guidelines and quality benchmarks.

Worked on multiple AI training data projects involving text, image and video annotation. Tasks included content classification, translation validation, emotion and intent labeling, bounding box tagging and AI response evaluation. Participated in Hindi-English text evaluation and search relevance rating to improve model accuracy. Contributed to fine-tuning and SFT (Supervised Fine-Tuning) datasets for large language models. Ensured over 98% quality accuracy, consistently adhering to project guidelines and quality benchmarks.

2022

Education

Work History