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Alan W.

Alan W.

Freelance Data Annotator (RLHF, Data Labeling) AI & Machine Learning, Technology

China flagwuhan, China

Key Skills

Software

No software listed

Top Subject Matter

I specialize in evaluating AI model responses (safety
factuality
instruction following)
text/image classification
quality assurance for training data. I am good at following detailed rubrics

Top Data Types

No data types listed

Top Task Types

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Freelancer Overview

my "training" involved processing vast amounts of data curated and labeled by teams of human annotators like you. High-quality data labeling is foundational—annotators help create supervised datasets for tasks such as instruction following, reasoning, safety alignment, and preference ranking. In my case, this includes everything from tagging text for factual accuracy and helpfulness to evaluating responses in reinforcement learning from human feedback (RLHF). Even as an entry-level annotator, your work directly shapes model behavior by identifying patterns, reducing biases, and ensuring outputs align with human values. My development emphasized scaling efficiently while maintaining truth-seeking and curiosity-driven responses. Annotators contribute by creating diverse examples, spotting edge cases, and providing consistent guidelines across languages and domains. Starting out, focus on precision, clear annotation rubrics, and iterative feedback loops—these make the biggest difference in training robust models. Your attention to detail today helps build more capable AI tomorrow. Keep learning the tools and quality standards; it’s a critical and rewarding field

Labeling Experience

As an entry-level Data Annotator, I have gained hands-on experience in labeling and annotating large datasets to support

As an entry-level Data Annotator, I have gained hands-on experience in labeling and annotating large datasets to support the training and improvement of AI and machine learning models. My responsibilities include performing accurate data tagging for tasks such as image classification, object detection (bounding boxes), semantic segmentation, and text annotation for NLP projects. I strictly follow annotation guidelines to ensure high-quality, consistent labeling while maintaining attention to detail and efficiency under tight deadlines. Through this role, I have developed a strong understanding of how high-quality training data directly impacts model performance. I am proficient in using common annotation tools and platforms, and I am continuously learning about AI fundamentals, data quality standards, and best practices in the field. This foundational experience has equipped me with the skills to contribute effectively to AI development teams and further grow in the data annotation and AI domain.

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Education

B

Baidu Data Labeling Specialist Certification (In Progress) – Online training program covering structured annotation guid

Degree not specified

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Work History

C

Company not specified

AI Data Annotation Specialist (Freelance) Self-employed / Remote Performed text/image classification and LLM response e

Location not specified
Not specified