Shreyas Kori

Key Skills

Software

CVAT

Doccano

Labelbox

LabelImg

Scale AI

Snorkel AI

SuperAnnotate

Supervisely

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Task Types

Bounding Box

Classification

Data Collection

Entity Ner Classification

Segmentation

Freelancer Overview

I am an AI Training Data Specialist with extensive experience in data labeling, annotation, and model evaluation across multiple domains. I have hands-on expertise with time-series data, text, and image/video datasets, applying techniques such as classification, entity recognition (NER), bounding boxes, segmentation, and time-series annotation. My background includes developing predictive models for mechanical systems, implementing RUL and probabilistic analysis, and enhancing data quality for machine learning pipelines. I have contributed to projects in predictive maintenance, risk assessment, and AI model training, ensuring high-quality labeled data for deep learning and NLP applications. Proficient with tools like CVAT, LabelImg, Doccano, and Python-based custom annotation pipelines, I bring a combination of technical depth, domain knowledge, and attention to detail that ensures accurate, consistent, and actionable training datasets for cutting-edge AI systems.

Labeling Experience

NLP & Text Data Annotation Specialist

DoccanoTextEntity Ner ClassificationSegmentation

Managed annotation of large-scale text datasets for AI model training, including technical reports, emails, and intelligence documents. Tasks included identifying key entities, classifying document types, and labeling sentiment or risk levels to support NLP and LLM evaluation. Developed custom scripts to automate repetitive labeling tasks, ensuring high accuracy and consistency. Collaborated with ML engineers to refine annotation guidelines and validate model outputs, contributing to improved AI model performance and reliability.

Managed annotation of large-scale text datasets for AI model training, including technical reports, emails, and intelligence documents. Tasks included identifying key entities, classifying document types, and labeling sentiment or risk levels to support NLP and LLM evaluation. Developed custom scripts to automate repetitive labeling tasks, ensuring high accuracy and consistency. Collaborated with ML engineers to refine annotation guidelines and validate model outputs, contributing to improved AI model performance and reliability.

2024 - 2024

Predictive Maintenance & RUL Data Annotation Specialist

CVATTextBounding BoxEntity Ner Classification

Led data labeling and annotation for a project focused on predictive maintenance of turbofan engines and industrial equipment. Responsibilities included annotating time-series sensor data for remaining useful life (RUL) prediction, classifying operational vs faulty states, and tagging key events for machine learning model training. Additionally, annotated technical reports and documentation using NER for risk assessment and intelligence analysis, ensuring high-quality datasets for deep learning models. Implemented custom Python pipelines to streamline annotation, reduce errors, and maintain consistency across large datasets.

Led data labeling and annotation for a project focused on predictive maintenance of turbofan engines and industrial equipment. Responsibilities included annotating time-series sensor data for remaining useful life (RUL) prediction, classifying operational vs faulty states, and tagging key events for machine learning model training. Additionally, annotated technical reports and documentation using NER for risk assessment and intelligence analysis, ensuring high-quality datasets for deep learning models. Implemented custom Python pipelines to streamline annotation, reduce errors, and maintain consistency across large datasets.

2023 - 2024

Education

Work History