Jaey L.

Key Skills

Software

Other

Anno-Mage

AWS SageMaker

CrowdSource

Data Annotation Tech

Top Subject Matter

Large language models (LLMs)

generative AI

and prompt evaluation

Top Data Types

Text

Document

Image

Top Task Types

RLHF

Entity (NER) Classification

Transcription

Evaluation/Rating

Computer Programming/Coding

Data Collection

Text Summarization

Text Generation

Function Calling

Red Teaming

Question Answering

Object Detection

Polyline

Classification

Cuboid

Point/Key Point

Fine-tuning

Segmentation

Polygon

Prompt + Response Writing (SFT)

Freelancer Overview

AI Data Annotator / AI Trainer – Outlier AI (Remote). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Science, Strayer University (2026). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and RLHF.

Labeling Experience

AI Training & Annotation Contributor – Handshake / Project Helix (Remote)

OtherTextRLHF

Contributed to AI model training initiatives through annotation, evaluation, and validation workflows. Assisted in identifying model failures and improving AI response quality across reasoning and technical tasks. Participated in reinforcement learning and LLM evaluation processes using prompt engineering and evaluation rubrics. • Annotation and validation for model training • Failure analysis to improve reasoning and technical responses • Prompt engineering guided by evaluation rubrics • Remote collaboration with documentation and testing systems

2025 - Present

AI Data Annotator / AI Trainer – Outlier AI (Remote)

OtherText

Provided AI data labeling, annotation, and quality evaluation for large language models and generative AI systems. Reviewed and rated AI-generated responses for accuracy, reasoning quality, and policy compliance while applying defined rubrics and guidelines. Conducted prompt evaluation, ranking, and reinforcement learning/human feedback-based tasks as part of training and validation workflows. • LLM and generative AI response rating for quality and compliance • Prompt evaluation and ranking for improved model behavior • Annotation using structured datasets and labeling tools • QA checks to meet performance and productivity benchmarks

2025 - Present

Education

Work History