Jhansi Rani

Key Skills

Software

AWS SageMaker

Appen

CrowdSource

CVAT

Data Annotation Tech

Dataloop

Google Cloud Vertex AI

Labelbox

Scale AI

Telus

V7 Labs

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Computer Code Programming

Document

Image

Text

Video

Top Label Types

Action Recognition

Audio Recording

Bounding Box

Classification

Computer Programming Coding

Emotion Recognition

Evaluation Rating

Fine Tuning

Geocoding

Mapping

Object Detection

Prompt Response Writing SFT

Question Answering

Red Teaming

Segmentation

Text Generation

Text Summarization

Transcription

Translation Localization

Freelancer Overview

I am an experienced ML Data Associate with a strong background in data labeling, annotation, and AI training data workflows. At Amazon, I have contributed to over 10 critical projects involving structured and unstructured data, including tasks like image, text, audio, and video annotation using tools such as AWS SageMaker Ground Truth. My expertise spans bounding box, segmentation, classification, and transcription tasks, where I consistently ensure high data quality through rigorous validation and adherence to annotation guidelines. I have experience collaborating closely with data scientists and AI engineers to optimize dataset accuracy and model performance, and have engineered LLM prompts and RAG implementations that improved model accuracy by 40%. My technical skills include AWS Cloud, MS Excel, and ERP systems, and I am adept at managing high-volume labeling tasks under tight deadlines while maintaining precision and consistency.

Labeling Experience

ML Data Associate II

Aws SagemakerImageBounding Box

Labeled and annotated structured and unstructured data including images, text, audio, and video for AI/ML model development. Ensured data quality through validation, quality checks, and consistent application of annotation guidelines. Collaborated with data scientists and AI engineers to enhance dataset quality and model accuracy. • Performed bounding box, segmentation, classification, and transcription tasks with high accuracy. • Maintained consistency and met tight deadlines working on high-volume datasets. • Participated in prompt engineering and RAG workflow implementations for advanced model training. • Utilized AWS SageMaker Ground Truth and Appen for efficient annotation processes.

Labeled and annotated structured and unstructured data including images, text, audio, and video for AI/ML model development. Ensured data quality through validation, quality checks, and consistent application of annotation guidelines. Collaborated with data scientists and AI engineers to enhance dataset quality and model accuracy. • Performed bounding box, segmentation, classification, and transcription tasks with high accuracy. • Maintained consistency and met tight deadlines working on high-volume datasets. • Participated in prompt engineering and RAG workflow implementations for advanced model training. • Utilized AWS SageMaker Ground Truth and Appen for efficient annotation processes.

2024

Education

Work History