Saurabh M.

Key Skills

Software

No software listed

Top Subject Matter

AI response evaluation and quality assurance

Text data annotation for AI training

Internet research

Top Data Types

Text

Top Task Types

Classification

Data Collection

Freelancer Overview

AI Content Evaluation Project (Reviewed and rated AI responses). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include N, A, and Google Sheets. Education includes Higher Secondary Education (12th), N/A. AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Freelance Data Entry & Online Research (Self-Employed)

TextData Collection

Collected information from online sources and organized it into structured records using spreadsheets. Verified and cleaned datasets to improve consistency and usability for data-related tasks. Conducted web research and information validation while following detailed task instructions. • Performed internet research and information validation. • Maintained structured spreadsheets with accurate records. • Verified and cleaned datasets for consistency. • Followed guidelines to complete data collection tasks reliably.

2024 - Present

Data Annotation Practice (Text annotation and labeling)

TextClassification

Annotated and labeled text data according to project requirements and dataset guidelines. Categorized content accurately and applied labels consistently to support downstream AI training. Maintained quality standards to ensure reliable dataset coverage and correctness. • Labeled text instances using predefined categories. • Categorized and tagged datasets with consistent label application. • Followed annotation instructions and quality criteria. • Checked outputs for consistency and correctness before completion.

2024 - Present

AI Content Evaluation Project (Reviewed and rated AI responses)

Text

Evaluated AI-generated responses for relevance, accuracy, and quality against predefined guidelines. Identified factual errors and other output issues, then provided improvement feedback to support model performance. Performed consistent review and rating across cases to maintain annotation standards. • Rated outputs according to project-specific scoring rules. • Flagged factual inaccuracies and quality defects. • Supplied actionable feedback to improve AI responses. • Ensured evaluations followed provided instructions and rubrics.

2024 - Present

Education

Work History