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Ayush Saini

Ayush Saini

Data Annotator – Lunar AI 'Fit Trip Tags'

India flagTiruchirappalli, India
$6.00/hrEntry LevelCVATLabelboxLabel Studio

Key Skills

Software

CVATCVAT
LabelboxLabelbox
Label StudioLabel Studio
SuperAnnotateSuperAnnotate
Other

Top Subject Matter

AI-driven travel recommendation
Legal Services & Contract Review
Regulatory Compliance & Risk Analysis

Top Data Types

ImageImage
TextText
DocumentDocument

Top Task Types

Bounding BoxBounding Box
ClassificationClassification
Object DetectionObject Detection

Freelancer Overview

Data Annotator – Lunar AI 'Fit Trip Tags'. Brings 7+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other. AI-training focus includes data types such as Text and labeling workflows including Classification.

Entry LevelHindiEnglish

Labeling Experience

Data Annotator – Lunar AI 'Fit Trip Tags'

OtherTextClassification
As a Data Annotator for Lunar AI's 'Fit Trip Tags' initiative, I contributed to a human-in-the-loop data labeling project enhancing AI recommendation models using InsideAirbnb datasets. My responsibilities included rapidly analyzing unstructured text and categorical data to classify short-term rental listings into detailed traveler profiles. I maintained high accuracy and speed, processing complex profiles within short evaluation windows. • Classified listings by traveler type using unstructured descriptions, amenities, and property types • Supported AI model training by providing clear traveler-target labels • Operated within tight timeframes to ensure both processing rate and precision targets • Enhanced model quality through nuanced tagging and careful evaluation

As a Data Annotator for Lunar AI's 'Fit Trip Tags' initiative, I contributed to a human-in-the-loop data labeling project enhancing AI recommendation models using InsideAirbnb datasets. My responsibilities included rapidly analyzing unstructured text and categorical data to classify short-term rental listings into detailed traveler profiles. I maintained high accuracy and speed, processing complex profiles within short evaluation windows. • Classified listings by traveler type using unstructured descriptions, amenities, and property types • Supported AI model training by providing clear traveler-target labels • Operated within tight timeframes to ensure both processing rate and precision targets • Enhanced model quality through nuanced tagging and careful evaluation

2026 - 2026

Research Intern

ImageClassification
As a Research Intern, I contributed to an ongoing project focused on CNC tool wear monitoring and predictive maintenance. My responsibilities involved comprehensive data analysis, machine learning model development, and extracting actionable insights from experimental results. This position required strong analytical skills, proficiency in Python and popular data science libraries, and the ability to derive technical conclusions for practical applications. • Led exploratory data analysis (EDA) and preprocessing of machining experiment data using Python, Pandas, and NumPy. • Engineered 28 data features and compiled an ML-ready dataset of over 17,500 records. • Benchmarked seven machine learning models for tool condition classification, achieving over 92% accuracy. • Developed wear-risk scoring and safe operating window analysis to inform predictive maintenance strategies.

As a Research Intern, I contributed to an ongoing project focused on CNC tool wear monitoring and predictive maintenance. My responsibilities involved comprehensive data analysis, machine learning model development, and extracting actionable insights from experimental results. This position required strong analytical skills, proficiency in Python and popular data science libraries, and the ability to derive technical conclusions for practical applications. • Led exploratory data analysis (EDA) and preprocessing of machining experiment data using Python, Pandas, and NumPy. • Engineered 28 data features and compiled an ML-ready dataset of over 17,500 records. • Benchmarked seven machine learning models for tool condition classification, achieving over 92% accuracy. • Developed wear-risk scoring and safe operating window analysis to inform predictive maintenance strategies.

2025 - 2026

Education

N

NIT, Trichy

Bachelor of Technology, Production Engineering

Bachelor of Technology
2023 - 2027
N

New Green Field School, Saket, Delhi

High School Diploma, Science

High School Diploma
2022 - 2022

Work History

F

FSOC Film Society

Content Contributor, Online Presence Team

Tiruchirappalli
2025 - 2026
P

Pragyan

Deputy Manager, Publicity Team

Tiruchirappalli
2025 - 2026