Narisety S.

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Top Task Types

Computer Programming/Coding

Text Generation

Text Summarization

Freelancer Overview

I have 2 years of hands-on experience in data labeling and AI training workflows, with a focus on enhancing the accuracy and performance of machine learning models. My work at Soul AI (2023–2024) involved building and curating high-quality datasets for supervised learning tasks, including image classification and NLP annotation. I utilized tools like Labelbox, CVAT, and custom Python scripts to ensure consistency, reduce labeling errors, and accelerate throughput. During my tenure at RWS (2024–2025), I contributed to AI model training for large language and vision models, refining data pipelines and applying best practices in data quality control, annotation guidelines, and versioning of datasets. My strengths lie in understanding the relationship between high-quality labeled data and model performance, ensuring that datasets are balanced, unbiased, and scalable. I’ve collaborated with data scientists and ML engineers to refine label taxonomies, perform quality audits, and iterate based on model feedback. With a solid foundation in Python, SQL, and ML fundamentals, I bring both technical and domain knowledge to bridge the gap between raw data and effective AI systems.

Labeling Experience

AI expert in RWS

Scale AIImageObject Detection

At RWS, I worked as an AI Expert contributing to the creation and curation of high-quality image datasets to train computer vision models. My responsibilities included annotating image data for classification and object detection tasks using the Scale AI platform. I ensured high annotation accuracy by following strict labeling guidelines, identifying edge cases, and correcting ambiguous or inconsistent labels. Additionally, I collaborated with QA teams to review dataset quality and implement feedback loops to refine label consistency. This project significantly contributed to improving the performance of AI models used in applications such as automated visual inspection and content moderation. My experience at RWS strengthened my ability to manage large-scale data labeling workflows while maintaining a high standard of precision and efficiency.

2024 - 2025

Education

Work History