Jane Zulu

Key Skills

Software

Other

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Label Types

Audio Recording

Bounding Box

Classification

Data Collection

Entity Ner Classification

Evaluation Rating

Prompt Response Writing SFT

RLHF

Transcription

Freelancer Overview

I’ve worked on AI training and data labeling projects through platforms like Outlier, Handshake AI, and Alignerr, where I supported large language model (LLM) improvement through structured annotation, response evaluation, and quality review tasks. My work involved grading model outputs against detailed rubrics, identifying inaccuracies or bias, ranking comparative responses, and ensuring strict adherence to platform guidelines. I consistently handled high-volume assignments while maintaining accuracy, clarity, and turnaround expectations in fast-paced environments. What sets me apart is my analytical background (M.S. in Business Analytics) combined with strong instruction adherence and attention to detail. I’m comfortable interpreting complex guidelines, identifying edge cases, and providing structured feedback to improve dataset quality. My experience with SQL and Python also gives me a deeper understanding of how labeled data feeds into model performance, allowing me to approach annotation tasks with both precision and broader system awareness.

Labeling Experience

Annotation & Alignment Contributor

LabelboxTextClassificationEvaluation Rating

My responsibilities centered on executing alignment and annotation workflows for improving AI model consistency and reliability. Structured categorization, labeling, and identification of edge cases played a core part in this position. All work was completed in compliance with strict platform-specific quality assurance frameworks. • Labeled, categorized, and aligned textual data in accordance with detailed frameworks. • Identified inconsistencies, ambiguous cases, and edge conditions for escalation. • Maintained rigorous quality standards across all annotation tasks. • Supported continuous enhancement of model reliability and coherence through systematic data preparation.

My responsibilities centered on executing alignment and annotation workflows for improving AI model consistency and reliability. Structured categorization, labeling, and identification of edge cases played a core part in this position. All work was completed in compliance with strict platform-specific quality assurance frameworks. • Labeled, categorized, and aligned textual data in accordance with detailed frameworks. • Identified inconsistencies, ambiguous cases, and edge conditions for escalation. • Maintained rigorous quality standards across all annotation tasks. • Supported continuous enhancement of model reliability and coherence through systematic data preparation.

2025 - 2025

AI Data Labeling Specialist

OtherTextRLHFEvaluation Rating

In this role, I completed text classification, comparative evaluations, and reinforcement learning from human feedback (RLHF) style grading of AI-generated responses. Outputs were meticulously assessed against rubrics to ensure alignment with predefined standards. Rigorous attention to consistency, rubric interpretation, and quality assurance was demonstrated. • Performed large-scale RLHF-style grading and text analysis tasks. • Evaluated and classified responses based on customized rubrics for accuracy and appropriateness. • Provided actionable feedback to improve model output quality. • Demonstrated strong pattern recognition and adherence to detailed task instructions.

In this role, I completed text classification, comparative evaluations, and reinforcement learning from human feedback (RLHF) style grading of AI-generated responses. Outputs were meticulously assessed against rubrics to ensure alignment with predefined standards. Rigorous attention to consistency, rubric interpretation, and quality assurance was demonstrated. • Performed large-scale RLHF-style grading and text analysis tasks. • Evaluated and classified responses based on customized rubrics for accuracy and appropriateness. • Provided actionable feedback to improve model output quality. • Demonstrated strong pattern recognition and adherence to detailed task instructions.

2025 - 2025

AI Training Contributor

OtherTextBounding BoxEntity Ner Classification

I completed structured annotation and evaluation assignments to enhance large language model performance. Tasks focused on carefully reviewing model-generated outputs for accuracy and adherence to detailed labeling guidelines. High standards for subjectivity, bias flagging, and turnaround were consistently maintained. • Consistently applied intricate labeling and evaluation schemas to high-volume text. • Flagged ambiguous or problematic model outputs and provided constructive feedback for continuous improvement. • Met demanding deadlines while maintaining elevated accuracy and quality benchmarks. • Enhanced dataset quality through comprehensive review and structured annotation.

I completed structured annotation and evaluation assignments to enhance large language model performance. Tasks focused on carefully reviewing model-generated outputs for accuracy and adherence to detailed labeling guidelines. High standards for subjectivity, bias flagging, and turnaround were consistently maintained. • Consistently applied intricate labeling and evaluation schemas to high-volume text. • Flagged ambiguous or problematic model outputs and provided constructive feedback for continuous improvement. • Met demanding deadlines while maintaining elevated accuracy and quality benchmarks. • Enhanced dataset quality through comprehensive review and structured annotation.

2025 - 2025

Education

Work History