Sanjay Bharti

Key Skills

Software

Scale AI

SuperAnnotate

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Text

Video

Top Label Types

Computer Programming Coding

Data Collection

Evaluation Rating

Object Detection

Prompt Response Writing SFT

RLHF

Freelancer Overview

With over 10 years of experience as a software engineer, I have worked extensively on projects involving large-scale healthcare and government data, where data accuracy, security, and integrity were essential. My background includes designing and developing user interfaces for data-intensive applications, integrating REST APIs for real-time data retrieval, and ensuring reliable data workflows across modules. I am highly proficient in JavaScript, TypeScript, Python, SQL, and data visualization tools like Tableau, and have hands-on experience with cloud services, API testing, and DevOps tools. My work on healthcare platforms required precise handling and presentation of sensitive data, which has strengthened my attention to detail and quality in data annotation and validation tasks. I am passionate about leveraging my technical skills to support high-quality data labeling and AI training data initiatives, especially in domains such as medical and geospatial data.

Labeling Experience

AI Data Annotator / QA Evaluator

Scale AITextEvaluation Rating

Served as an AI Data Annotator and QA Evaluator at Outlier AI, focusing on text-based annotation and evaluation for AI/LLM models. Tasks included response rating, summarization evaluation, and intent labeling with defined guidelines. Structured formats such as JSON and YAML were utilized to define test cases and validation rules. Worked collaboratively to improve model performance by providing feedback on hallucinations and inconsistencies. • Annotated and reviewed AI-generated outputs and agent logs. • Created evaluation scenarios and documented edge cases. • Designed and applied scoring rubrics. • Flagged issues related to logical inconsistencies and formatting.

Served as an AI Data Annotator and QA Evaluator at Outlier AI, focusing on text-based annotation and evaluation for AI/LLM models. Tasks included response rating, summarization evaluation, and intent labeling with defined guidelines. Structured formats such as JSON and YAML were utilized to define test cases and validation rules. Worked collaboratively to improve model performance by providing feedback on hallucinations and inconsistencies. • Annotated and reviewed AI-generated outputs and agent logs. • Created evaluation scenarios and documented edge cases. • Designed and applied scoring rubrics. • Flagged issues related to logical inconsistencies and formatting.

2024 - 2025

Education

Work History