Rammani Pandey

Key Skills

Software

Other

Google Cloud Vertex AI

Top Subject Matter

Large Language Models (LLMs)

AI Evaluation

Computer Vision

Top Data Types

Text

Image

Document

Top Task Types

Entity Ner Classification

Freelancer Overview

AI QA Analyst – Scaler (InterviewBit) AI Lab. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Bachelor of Technology, AKS University, Satna (2024) and Higher Secondary School Certificate, Saraswati Chanakyapuri -HSS- (Mathematics) School, Rewa (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Entity (NER) Classification.

Labeling Experience

AI QA Analyst – Scaler (InterviewBit) AI Lab

Text

As an AI QA Analyst at Scaler (InterviewBit) AI Lab, I performed comprehensive validation and quality evaluation of AI-generated outputs. My role focused on grounding analysis, hallucination detection, and maintaining strict quality benchmarks across LLM-based projects. I ensured operational accuracy by identifying inconsistencies in datasets affecting model performance. • Conducted systematic evaluation of LLM outputs for relevance and grounding. • Detected hallucinations in AI responses, addressing factual inaccuracies. • Maintained operational accuracy and stringent quality standards. • Identified and reported dataset inconsistencies for model improvement.

As an AI QA Analyst at Scaler (InterviewBit) AI Lab, I performed comprehensive validation and quality evaluation of AI-generated outputs. My role focused on grounding analysis, hallucination detection, and maintaining strict quality benchmarks across LLM-based projects. I ensured operational accuracy by identifying inconsistencies in datasets affecting model performance. • Conducted systematic evaluation of LLM outputs for relevance and grounding. • Detected hallucinations in AI responses, addressing factual inaccuracies. • Maintained operational accuracy and stringent quality standards. • Identified and reported dataset inconsistencies for model improvement.

2025 - Present

AI/LLM Analyst – Data Annotator (Freelance, Remote)

OtherTextEntity Ner Classification

As an AI/LLM Analyst and Data Annotator (Freelance), I annotated various datasets spanning text, images, and videos for computer vision and LLM projects. The primary focus was on entity tagging, dataset validation, and content moderation tasks to support model training and evaluation. Ensuring contextual relevance and factual accuracy was a critical aspect of my responsibilities. • Annotated and labeled data to meet project guidelines and requirements. • Evaluated AI outputs for relevance and factual correctness. • Performed content moderation and cleaned datasets for compliance. • Maintained a high accuracy standard (>95%) in annotations and evaluations.

As an AI/LLM Analyst and Data Annotator (Freelance), I annotated various datasets spanning text, images, and videos for computer vision and LLM projects. The primary focus was on entity tagging, dataset validation, and content moderation tasks to support model training and evaluation. Ensuring contextual relevance and factual accuracy was a critical aspect of my responsibilities. • Annotated and labeled data to meet project guidelines and requirements. • Evaluated AI outputs for relevance and factual correctness. • Performed content moderation and cleaned datasets for compliance. • Maintained a high accuracy standard (>95%) in annotations and evaluations.

2025 - 2026

Google Cloud AI/LLM Practitioner – GenAI, Prompt Engineering & Model Evaluation (Remote)

Google Cloud Vertex AIText

As a Google Cloud AI/LLM Practitioner, I engaged in 12 months of hands-on GenAI and LLM-related project tracks. My tasks included evaluating and deploying ML/AI models, exploring generative workflows, and testing AI-powered applications. The experience spanned model quality assessment and experimentation with Vertex AI and related ML APIs. • Built and deployed ML and LLM solutions on Google Cloud. • Evaluated model validity, performance, and generative outputs. • Worked with Vertex AI and ML APIs for LLM evaluation. • Gained experience in GenAI workflows and model deployment in practice.

As a Google Cloud AI/LLM Practitioner, I engaged in 12 months of hands-on GenAI and LLM-related project tracks. My tasks included evaluating and deploying ML/AI models, exploring generative workflows, and testing AI-powered applications. The experience spanned model quality assessment and experimentation with Vertex AI and related ML APIs. • Built and deployed ML and LLM solutions on Google Cloud. • Evaluated model validity, performance, and generative outputs. • Worked with Vertex AI and ML APIs for LLM evaluation. • Gained experience in GenAI workflows and model deployment in practice.

2024 - 2025

Education

Work History