Anurag K.

Key Skills

Software

AWS SageMaker

Labelbox

Scale AI

SuperAnnotate

Label Studio

Top Subject Matter

Data science and machine learning (preprocessing/modeling)

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Action Recognition

Computer Programming/Coding

Prompt + Response Writing (SFT)

Text Generation

Freelancer Overview

Data Science Intern at AU IGNITE (Jan 2024 – Apr 2024). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include N and A. Education includes Bachelor of Technology, Arya Institute of Engineering Technology and Management (2024). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Computer Programming and Coding.

Labeling Experience

Multilingual Static Comparison V2 Instructions

Scale AITextEvaluation/Rating

The Multilingual Static Comparison V2 project involves evaluating and comparing AI-generated responses in multiple languages. Human reviewers assess two AI responses to the same user prompt, identify issues, rank their quality, and rewrite responses when both are subpar. The project focuses on entertainment-style conversational AI and requires reviewers to ensure responses are natural, engaging, culturally appropriate, and aligned with the AI character’s persona.

2025

Code Snippet Classification and Annotation

Label StudioComputer Code ProgrammingPrompt + Response Writing (SFT)

Annotated 15,000+ Python code snippets for an AI coding assistant. Labeled function types, variables, and bugs using tools like Label Studio and custom Python scripts. Helped improve model accuracy in code understanding and autocompletion by 20%.

2024

Data Science Intern at AU IGNITE (Jan 2024 – Apr 2024)

Worked on data modeling and machine learning tasks as part of a data science internship, which involved preparing datasets for analytics and model development. Performed data cleaning and anomaly detection to improve data quality prior to downstream modeling and evaluation. Applied these steps to solve real-world analytics problems tied to AI workflows. • Data cleaning and preprocessing • Anomaly detection on datasets • Data modeling for ML workflows • Real-world analytics problem solving

2024 - 2024

Education

Work History