Ravi N.

Key Skills

Software

Appen

Labelbox

Label Studio

Remotasks

SuperAnnotate

Telus

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Task Types

Classification

Emotion Recognition

Evaluation/Rating

Prompt + Response Writing (SFT)

Translation/Localization

Freelancer Overview

I am an entry-level AI data labeling specialist with growing experience in text evaluation, sentiment analysis, and content categorization. My bilingual fluency in English and Hindi helps me accurately assess and annotate text data for various AI projects. I have practiced labeling through small-scale training exercises and familiarized myself with platforms like Appen, TELUS International, and Remotasks. With a Commerce background, I bring strong analytical thinking and attention to detail, which are crucial for maintaining labeling accuracy and consistency. I am eager to contribute to projects that involve text classification, evaluation of AI-generated content, and English–Hindi translation tasks. I continuously improve my understanding of labeling standards, quality checks, and annotation tools such as Label Studio and Labelbox.

Labeling Experience

Python Code Review and Classification (Practice Project)

Label StudioComputer Code ProgrammingEvaluation RatingComputer Programming Coding

Worked on practice datasets involving Python code snippets. Reviewed short Python scripts, identified syntax and logic errors, and categorized outputs as correct or incorrect. Rated AI-generated coding responses for clarity, correctness, and performance. Developed a solid understanding of Python functions, loops, and data structures to support model evaluation accuracy.

Worked on practice datasets involving Python code snippets. Reviewed short Python scripts, identified syntax and logic errors, and categorized outputs as correct or incorrect. Rated AI-generated coding responses for clarity, correctness, and performance. Developed a solid understanding of Python functions, loops, and data structures to support model evaluation accuracy.

2025 - 2025

Image Tagging and Object Annotation (Basic Training)

Label StudioImageBounding BoxSegmentation

Practiced basic image tagging and object annotation using demo datasets focused on identifying everyday objects, vehicles, and household items. Drew bounding boxes and assigned category labels to visual elements within images. Developed an understanding of key annotation techniques, labeling accuracy, and quality control processes used in image datasets for computer vision model training. Learned how to handle diverse image types, maintain annotation consistency, and meet labeling standards. Applied visual attention and precision to ensure that all tagged objects were correctly aligned and categorized.

Practiced basic image tagging and object annotation using demo datasets focused on identifying everyday objects, vehicles, and household items. Drew bounding boxes and assigned category labels to visual elements within images. Developed an understanding of key annotation techniques, labeling accuracy, and quality control processes used in image datasets for computer vision model training. Learned how to handle diverse image types, maintain annotation consistency, and meet labeling standards. Applied visual attention and precision to ensure that all tagged objects were correctly aligned and categorized.

2025 - 2025

English–Hindi Translation and Content Evaluation

TelusTextQuestion AnsweringText Generation

Conducted bilingual text evaluation tasks involving English–Hindi translations for AI model training. Reviewed, corrected, and rated AI-generated translations for grammatical accuracy, fluency, and contextual meaning. Evaluated quality of machine-generated responses in both languages, ensuring natural tone and proper translation of idiomatic expressions. Developed understanding of linguistic nuances, cultural context, and sentence structure used in NLP datasets. Focused on maintaining quality consistency and accurate alignment of source and translated text during annotation.

Conducted bilingual text evaluation tasks involving English–Hindi translations for AI model training. Reviewed, corrected, and rated AI-generated translations for grammatical accuracy, fluency, and contextual meaning. Evaluated quality of machine-generated responses in both languages, ensuring natural tone and proper translation of idiomatic expressions. Developed understanding of linguistic nuances, cultural context, and sentence structure used in NLP datasets. Focused on maintaining quality consistency and accurate alignment of source and translated text during annotation.

2025 - 2025

Text Classification and Sentiment Labeling Practice

AppenImageClassificationEmotion Recognition

Worked on text labeling practice projects focused on English sentence classification and sentiment analysis. Labeled text data by identifying tone, intent, and sentiment (positive, negative, or neutral). Evaluated text accuracy and contextual meaning for AI model improvement. Ensured labeling consistency and adherence to project guidelines. Gained practical experience in English text understanding, emotion tagging, and data validation for AI training datasets.

Worked on text labeling practice projects focused on English sentence classification and sentiment analysis. Labeled text data by identifying tone, intent, and sentiment (positive, negative, or neutral). Evaluated text accuracy and contextual meaning for AI model improvement. Ensured labeling consistency and adherence to project guidelines. Gained practical experience in English text understanding, emotion tagging, and data validation for AI training datasets.

2025 - 2025

Education

Work History