James

Key Skills

Software

AWS SageMaker

Anno-Mage

Appen

Argilla

Top Subject Matter

AI response evaluation and multilingual (Chinese-English) quality assessment

LLM training data preparation for SFT/RLHF (prompt/response, labels, categories, quality checks)

Top Data Types

Text

Image

Video

Top Task Types

Prompt + Response Writing (SFT)

Fine-tuning

RLHF

Object Detection

Text Generation

Question Answering

Freelancer Overview

Bilingual AI Data Annotation & AI Evaluation Freelancer (AI response evaluation, ranking, and guideline-based quality re. Core strengths include ChatGPT, Codex, and Claude. Education includes Bachelor of Science . AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

AI Training Data & Annotation Practice (SFT/RLHF data support and structured text labeling)

OtherTextPrompt + Response Writing (SFT)Fine-tuning

Freelance support for AI training data preparation by transforming raw text materials into structured, label-ready datasets. The work covers constructing prompt/response pairs, applying labels and categories, and maintaining annotation guideline compliance for downstream SFT/RLHF workflows. Outputs are organized for consistent delivery and iterative improvement. • Convert raw documents into annotatable units including prompt, response, labels, and categories. • Apply SFT/RLHF data preparation steps such as rule documentation, label management, and iteration/review loops. • Perform text classification, tagging, and data cleaning to ensure high-quality training inputs. • Provide multi-language (Chinese-English) annotation in a guideline-based format.

2025 - Present

Bilingual AI Data Annotation & AI Evaluation Freelancer (AI response evaluation, ranking, and guideline-based quality review)

Don't discloseText

Bilingual AI data evaluation freelancer focused on assessing AI-generated outputs against structured guidelines and quality dimensions. Responsibilities include comparing multiple responses, verifying information using web research, and performing content审核/文本质量 checks to ensure consistent results. Work includes delivering organized evaluation outputs for training and iteration use. • Evaluate responses across usefulness, accuracy, safety, completeness, and instruction-following dimensions. • Conduct preference comparison, ranking, and answer ordering for RLHF-style feedback. • Support text quality review and information extraction/verification from multilingual sources. • Use spreadsheet-based organization and AI-assisted reading to maintain format consistency.

2025 - Present

Education

Work History