Sankar Chinnakotla

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Top Label Types

Fine Tuning

Evaluation Rating

Computer Programming Coding

Prompt Response Writing SFT

Freelancer Overview

With over 25 years of IT experience, I bring a strong technical background and hands-on expertise in data processing, automation, and integration—skills that are directly relevant to data labeling and AI training data projects. I have extensive experience working with Google Apps Script, Looker Studio, Google Sheets, and various APIs, enabling me to automate data workflows, ensure data quality, and build tools for data annotation and validation. My work spans diverse domains such as e-commerce, CRM, and custom automation, where I have delivered solutions involving web scraping, data transformation, and connector development. I am committed to delivering high-quality, detail-oriented results and excel at collaborating with cross-functional teams to meet project goals efficiently.

Labeling Experience

AI Model Trainer (Anthropic/Claude/Alignerr)

LabelboxComputer Code ProgrammingFine TuningEvaluation Rating

I participated in AI model training for Anthropic's Claude Model, evaluating model outputs and guiding iterative improvements through structured prompts. I compared generated solutions against expected results, rated model performance across multiple criteria, and selected the optimal model in each round. My work contributed to refining model readiness for production deployment. • Evaluated AI responses to code challenges and feature enhancements. • Provided guidance to elevate model outputs to production standards. • Compared multiple models and curated best-performing responses for further development. • Created documentation of performance metrics and improvement suggestions.

I participated in AI model training for Anthropic's Claude Model, evaluating model outputs and guiding iterative improvements through structured prompts. I compared generated solutions against expected results, rated model performance across multiple criteria, and selected the optimal model in each round. My work contributed to refining model readiness for production deployment. • Evaluated AI responses to code challenges and feature enhancements. • Provided guidance to elevate model outputs to production standards. • Compared multiple models and curated best-performing responses for further development. • Created documentation of performance metrics and improvement suggestions.

2025

Education

Work History