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ruslandavidenko/README.md

AI Annotation QA System

Quality Assurance & Evaluation Workflows for AI Training Pipelines

AI annotation quality assurance workflows for ranking, relevance scoring, factuality checks, and safety evaluation.

🔍 Overview

This repository contains AI annotation QA and evaluation workflows used for validating AI-generated outputs and human feedback pipelines.

Focused areas include:

  • Ranking systems
  • Relevance evaluation
  • Safety review
  • Hallucination detection
  • Human feedback alignment

🔧 Features

  • Annotation validation workflows
  • Evaluation scoring systems
  • AI safety checks
  • Quality benchmarking
  • Structured reporting pipelines
  • Human feedback integration

🛠️ Tech Stack

Python • Pandas • NumPy • OpenAI API • NLP Tooling • Evaluation Pipelines

🚀 Use Cases

  • RLHF workflows
  • LLM evaluation
  • Human annotation review
  • Safety benchmarking
  • Response quality analysis

📈 Planned Additions

  • Evaluation scripts
  • Notebook demos
  • Annotation dashboards
  • Scoring visualizations
  • Benchmark reports

📌 Status

🚧 Active Development

👨‍💻 Author

Ruslan Davidenko
AI Systems & Evaluation Engineer

Portfolio:
https://ruslandavidenko.github.io/

Pinned Loading

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