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Narendra Vemula

Narendra Vemula

AI Data Labeling & LLM Evaluation Specialist

INDIA flag
Mohali, India
$10.00/hrIntermediateAppenLabel StudioMercor

Key Skills

Software

AppenAppen
Label StudioLabel Studio
MercorMercor
ProdigyProdigy
Scale AIScale AI
Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage
TextText
VideoVideo

Top Label Types

Classification
Translation Localization
RLHF
Fine Tuning
Evaluation Rating

Freelancer Overview

I am a Computer Science undergraduate with strong hands-on experience in backend systems, database integration, and data management, graduating in 2026. My background in Java, SQL, MySQL, and JDBC has equipped me with a solid understanding of structured data handling, validation, and transaction management—skills that are directly applicable to data labeling and AI training data workflows. I have engineered projects involving complex workflow engines and custom connection pool managers, emphasizing data consistency, schema design, and the integrity of large datasets. My attention to detail, analytical thinking, and collaborative approach help me ensure high-quality, reliable data processes, making me well-suited for roles in data annotation and AI data preparation.

IntermediateEnglishTelugu

Labeling Experience

LLM Data Annotation Framework Project

Internal Proprietary ToolingTextEvaluation Rating
For the LLM Data Annotation Framework project, I crafted structured evaluation prompts to assess Telugu responses for contextual fit and localization. I executed systematic editing checks to discover clarity gaps, idiomatic inconsistencies, and language standard deviations. I documented thorough review outcomes to enable repeatable validation and cross-functional teamwork. • Designed prompt-based checks for localization and suitability across various use-cases. • Identified and cataloged clarity or language standard issues in model outputs. • Maintained detailed documentation for each annotation and validation cycle. • Supported distributed collaboration through structured reporting and workflow tools.

For the LLM Data Annotation Framework project, I crafted structured evaluation prompts to assess Telugu responses for contextual fit and localization. I executed systematic editing checks to discover clarity gaps, idiomatic inconsistencies, and language standard deviations. I documented thorough review outcomes to enable repeatable validation and cross-functional teamwork. • Designed prompt-based checks for localization and suitability across various use-cases. • Identified and cataloged clarity or language standard issues in model outputs. • Maintained detailed documentation for each annotation and validation cycle. • Supported distributed collaboration through structured reporting and workflow tools.

2025

GenAI Data Labeler and AI Response Evaluator — Outlier AI (Contract)

Internal Proprietary ToolingTextClassificationTranslation Localization
As a GenAI Data Labeler and AI Response Evaluator at Outlier AI, I annotated AI-generated Telugu and English responses for intent, sentiment, and contextual suitability to train and evaluate LLM datasets. I maintained rigorous quality assurance by applying rubric-based criteria to validate factual accuracy, language clarity, and dataset consistency. I ensured high annotation accuracy by following structured guidelines in a remote, deadline-driven setting. • Annotated AI-generated interactions for intent, sentiment, linguistic quality, and relevance. • Applied guideline-based rubric scoring for evaluation and grading of responses in Telugu and English. • Conducted systematic quality assurance to enhance dataset consistency and bias detection. • Utilized web-based annotation platforms and spreadsheets for documentation and tracking.

As a GenAI Data Labeler and AI Response Evaluator at Outlier AI, I annotated AI-generated Telugu and English responses for intent, sentiment, and contextual suitability to train and evaluate LLM datasets. I maintained rigorous quality assurance by applying rubric-based criteria to validate factual accuracy, language clarity, and dataset consistency. I ensured high annotation accuracy by following structured guidelines in a remote, deadline-driven setting. • Annotated AI-generated interactions for intent, sentiment, linguistic quality, and relevance. • Applied guideline-based rubric scoring for evaluation and grading of responses in Telugu and English. • Conducted systematic quality assurance to enhance dataset consistency and bias detection. • Utilized web-based annotation platforms and spreadsheets for documentation and tracking.

2023

Education

C

Chandigarh University

Bachelor of Engineering, Computer Science and Engineering

Bachelor of Engineering
2022 - 2025
S

Sri Gayatri Junior College

Class XII, Science

Class XII
2020 - 2022

Work History

O

Outlier AI

GenAI Data Labeler and AI Response Evaluator

Mohali
2023 - 2025