Yangtze

Key Skills

Software

CrowdSource

CloudFactory

CrowdFlower

Google Cloud Vertex AI

Top Subject Matter

Large Language Models (LLMs) and AI Model Alignment

Large Language Models (LLMs) and AI Data Annotation Research

Top Data Types

Text

Image

Document

Top Task Types

Bounding Box

Segmentation

Entity (NER) Classification

Polyline

Object Detection

Question Answering

Fine-tuning

Transcription

Computer Programming/Coding

Freelancer Overview

LLM Output Evaluation and AI Training Data Annotation Specialist. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Master of Computer Technology, Chongqing Normal University (2026). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Data Annotation and LLM Evaluation Contributor (Graduate Research)

Text

Executed LLM output evaluation and annotation for AI training data production projects. Produced high-quality dialogue annotations, preference rankings, and RLHF data in support of model development and improvement. Applied best practices in annotation quality control and prompt optimization within academic settings. • Ensured logical consistency and factual accuracy across annotated outputs for diverse LLM tasks. • Participated in prompt engineering experiments and research-focused evaluation workflows. • Provided technical input on annotation process improvement for LLM-related coursework and projects. • Adopted proven data processing and quality assurance methodologies for academic AI research.

2023 - Present

LLM Output Evaluation and AI Training Data Annotation Specialist

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Responsible for quality assurance and evaluation of large language model (LLM) outputs for AI applications. Tasks included designing and executing test cases for LLM question answering, dialogue annotation, and document processing scenarios. Performed data annotation, preference ranking, and response scoring according to set quality control standards. • Conducted structured scenario analyses to ensure annotation quality for diverse LLM use-cases. • Oversaw RLHF data processing and annotation quality control to optimize model behavior. • Leveraged technical skills in prompt engineering to assess logical consistency and factual accuracy of model outputs. • Collaborated with cross-functional teams to enhance annotation guidelines and streamline workflow.

2025 - 2026

Education

Work History