Purity Musambi

Key Skills

Software

Labelbox

Top Subject Matter

AI/LLM Training Data

LLM Prompt Engineering & Trajectory Evaluation

LLM Output Assessment & Annotation

Top Data Types

Text

Image

Document

Top Task Types

RLHF

Prompt Response Writing SFT

Freelancer Overview

AI Training & Data Annotation Specialist | RWS — Remote. Brings 4+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include RWS, Internal, and Proprietary Tooling. Education includes Bachelor of Science, Kenyatta University (2024) and Data Science Program, ALX Africa (2023). AI-training focus includes data types such as Text and labeling workflows including RLHF, Prompt + Response Writing (SFT), and Evaluation.

Labeling Experience

AI Training & Data Annotation Specialist | RWS — Remote

TextRLHF

Produced and validated annotation workflows for large-scale LLM training datasets spanning text, audio, image, and multimodal formats. Applied RLHF evaluation consistently across high-volume datasets to maintain quality and productivity thresholds. Designed and refined evaluation rubrics, annotation schemas, and quality SOPs in annotation workflows. • Provided corrective feedback to iteratively improve function-calling outputs • Identified errors and reasoning gaps in structured agent outputs • Supported model development with thorough evaluation documentation • Quickly adapted to evolving guidelines and task specifications.

Produced and validated annotation workflows for large-scale LLM training datasets spanning text, audio, image, and multimodal formats. Applied RLHF evaluation consistently across high-volume datasets to maintain quality and productivity thresholds. Designed and refined evaluation rubrics, annotation schemas, and quality SOPs in annotation workflows. • Provided corrective feedback to iteratively improve function-calling outputs • Identified errors and reasoning gaps in structured agent outputs • Supported model development with thorough evaluation documentation • Quickly adapted to evolving guidelines and task specifications.

2025 - Present

Prompt Engineering Intern | RIT & Excellerate — Remote

TextPrompt Response Writing SFT

Designed, tested, and validated prompt architectures for research-oriented, multi-step reasoning tasks and LLM trajectory creation. Evaluated and improved trajectory quality with a focus on reasoning depth, correctness, and alignment using structured analytical approaches. Engineered agentic workflows integrating multiple LLMs for automation and complex reasoning. • Documented prompt workflow logic and decisions for transparency • Achieved 98% instructional alignment and quality for experimental design tasks • Reduced AI verbosity through targeted prompt interventions • Delivered outputs in a remote, experimental AI training context.

Designed, tested, and validated prompt architectures for research-oriented, multi-step reasoning tasks and LLM trajectory creation. Evaluated and improved trajectory quality with a focus on reasoning depth, correctness, and alignment using structured analytical approaches. Engineered agentic workflows integrating multiple LLMs for automation and complex reasoning. • Documented prompt workflow logic and decisions for transparency • Achieved 98% instructional alignment and quality for experimental design tasks • Reduced AI verbosity through targeted prompt interventions • Delivered outputs in a remote, experimental AI training context.

2026 - 2026

AI Data Annotator & Content Evaluator | Labelbox · Appen · Crowdgen — Remote (Contract)

LabelboxText

Completed annotation and evaluation tasks for multiple AI/ML projects, focusing on multi-step reasoning and output validation. Assessed LLM outputs for reasoning depth, correctness, and task alignment across diverse research tasks. Adapted to changing evaluation criteria within AI labs’ quality frameworks. • Built proficiency with Labelbox, Appen, and Crowdgen across varied annotation projects • Managed outputs for evolving goals and formats • Performed in contract roles for multiple leading AI data platforms • Gained rapid fluency in diverse annotation and evaluation SOPs.

Completed annotation and evaluation tasks for multiple AI/ML projects, focusing on multi-step reasoning and output validation. Assessed LLM outputs for reasoning depth, correctness, and task alignment across diverse research tasks. Adapted to changing evaluation criteria within AI labs’ quality frameworks. • Built proficiency with Labelbox, Appen, and Crowdgen across varied annotation projects • Managed outputs for evolving goals and formats • Performed in contract roles for multiple leading AI data platforms • Gained rapid fluency in diverse annotation and evaluation SOPs.

2025 - 2025

Education

Work History