Anurag Sharma

Key Skills

Software

Mercor

Top Subject Matter

Sports Analytics/Cricket

General Language Model Responses

Top Data Types

Text

Top Task Types

RLHF

Freelancer Overview

AI Evaluator (Cricket). Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mercor. Education includes Bachelor of Technology, Gurugram University (2023) and Senior Secondary School Certificate, Central Board of Secondary Education (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and RLHF.

Labeling Experience

AI Evaluator (Cricket)

MercorText

As an AI Evaluator for cricket analysis, I assessed AI-generated sports analytics for real-world applicability. My primary responsibility was to review, rate, and provide feedback on scenario-based outputs and model decision-making. I focused on ensuring that AI responses met client expectations regarding accuracy and reasoning quality. • Evaluated AI-generated cricket analysis for accuracy and insights. • Provided scenario-based feedback to improve model reasoning. • Identified and corrected deficiencies in tactical outputs. • Collaborated with other evaluators to benchmark decision patterns.

As an AI Evaluator for cricket analysis, I assessed AI-generated sports analytics for real-world applicability. My primary responsibility was to review, rate, and provide feedback on scenario-based outputs and model decision-making. I focused on ensuring that AI responses met client expectations regarding accuracy and reasoning quality. • Evaluated AI-generated cricket analysis for accuracy and insights. • Provided scenario-based feedback to improve model reasoning. • Identified and corrected deficiencies in tactical outputs. • Collaborated with other evaluators to benchmark decision patterns.

2026 - Present

RLHF Generalist

MercorTextRLHF

In the RLHF Generalist position, I evaluated responses from large language models for quality. This work involved adversarial testing and identifying model weaknesses to improve overall output robustness. I was responsible for correcting hallucinations, unsafe content, and factual errors. • Evaluated LLM outputs for accuracy, safety, and tone. • Performed adversarial prompt testing to identify edge cases. • Flagged bias and reasoning deficiencies in model replies. • Improved model reliability by addressing hallucinations and errors.

In the RLHF Generalist position, I evaluated responses from large language models for quality. This work involved adversarial testing and identifying model weaknesses to improve overall output robustness. I was responsible for correcting hallucinations, unsafe content, and factual errors. • Evaluated LLM outputs for accuracy, safety, and tone. • Performed adversarial prompt testing to identify edge cases. • Flagged bias and reasoning deficiencies in model replies. • Improved model reliability by addressing hallucinations and errors.

2026 - 2026

Education

Work History