Liam Campbell

Key Skills

Software

Scale AI

Labelbox

Top Subject Matter

E-commerce Product Data & Taxonomy

Marketing Domain Expertise

Sales Domain Expertise

Top Data Types

Text

Image

Top Task Types

RLHF

Classification

Freelancer Overview

AI Data Annotator / Tasker. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Amazon MTurk, Scale AI, and Labelbox. Education includes Bachelor's Degree, N/A (2022). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and RLHF.

Labeling Experience

Annotation Specialist

LabelboxTextClassification

Executed structured annotation workflows across text and multimodal datasets for enterprise AI training. Labeled and categorized content spanning business, finance, SaaS, science, and office domains. Identified and flagged labeling edge cases to ensure annotation accuracy and consistency teamwide. • Used Labelbox's enterprise platform for annotation and quality control • Participated in calibration sessions to improve group reliability • Labeled both textual data and cross-domain datasets • Maintained annotation quality across verified expert fields assigned by the platform.

Executed structured annotation workflows across text and multimodal datasets for enterprise AI training. Labeled and categorized content spanning business, finance, SaaS, science, and office domains. Identified and flagged labeling edge cases to ensure annotation accuracy and consistency teamwide. • Used Labelbox's enterprise platform for annotation and quality control • Participated in calibration sessions to improve group reliability • Labeled both textual data and cross-domain datasets • Maintained annotation quality across verified expert fields assigned by the platform.

2023 - Present

AI Trainer / Content Evaluator

Scale AITextRLHF

Specialized in reinforcement learning from human feedback (RLHF) annotation to improve large language model performance. Ranked and annotated model-generated responses for accuracy, safety, tone, and helpfulness, providing critical human guidance. Participated in iterative quality-review cycles and contributed calibration notes to enhance team labeling accuracy. • Evaluated persuasive quality and clarity of model outputs in various contexts • Provided structured feedback on model errors and edge cases • Flagged inappropriate or manipulative content using expertise in consumer psychology • Utilized Scale AI's labeling platform for annotation workflow management.

Specialized in reinforcement learning from human feedback (RLHF) annotation to improve large language model performance. Ranked and annotated model-generated responses for accuracy, safety, tone, and helpfulness, providing critical human guidance. Participated in iterative quality-review cycles and contributed calibration notes to enhance team labeling accuracy. • Evaluated persuasive quality and clarity of model outputs in various contexts • Provided structured feedback on model errors and edge cases • Flagged inappropriate or manipulative content using expertise in consumer psychology • Utilized Scale AI's labeling platform for annotation workflow management.

2023 - Present

AI Data Annotator / Tasker

Text

Performed high-volume evaluation and annotation of text data for natural language processing training pipelines. Maintained top-tier acceptance rates by following strict annotation guidelines and delivering consistent, high-quality outputs. Rated and classified AI-generated content for clarity, persuasion, logical consistency, and accuracy. • Focused on response quality, tone, helpfulness, and safety in RLHF tasks • Contributed to prompt classification and intent judgment projects • Delivered nuanced feedback across domains like e-commerce, sales, and conversational AI • Used platforms such as Amazon MTurk for task management and delivery.

Performed high-volume evaluation and annotation of text data for natural language processing training pipelines. Maintained top-tier acceptance rates by following strict annotation guidelines and delivering consistent, high-quality outputs. Rated and classified AI-generated content for clarity, persuasion, logical consistency, and accuracy. • Focused on response quality, tone, helpfulness, and safety in RLHF tasks • Contributed to prompt classification and intent judgment projects • Delivered nuanced feedback across domains like e-commerce, sales, and conversational AI • Used platforms such as Amazon MTurk for task management and delivery.

2022 - Present

Education

Work History