Daniel N.

Key Skills

Software

Sama

Top Subject Matter

LLM Alignment

Generative AI

Human-AI Interaction

Top Data Types

Text

Document

Top Task Types

RLHF

Fine-tuning

Classification

Freelancer Overview

Senior Data Annotation Specialist. Brings 7+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Sama. Education includes Master of Science, University of Nairobi (2021) and Bachelor of Science, Jomo Kenyatta University of Agriculture and Technology (2017). AI-training focus includes data types such as Text and labeling workflows including RLHF, Fine-tuning, and Classification.

Labeling Experience

Senior Data Annotation Specialist

TextRLHF

As Senior Data Annotation Specialist, I curated high-quality training datasets for LLM fine-tuning and RLHF projects. I designed annotation rubrics for multi-turn dialogues and refined dataset integrity for generative AI models. My work enhanced safety, alignment, and performance through complex reasoning tasks. • Developed RLHF workflows and policies. • Documented edge cases and logical inconsistencies. • Ensured 100% adherence to strict annotation standards. • Drove improvements in LLM performance with precise data labeling.

2024 - 2025

LLM Training Data Researcher

TextFine-tuning

As LLM Training Data Researcher, I led the development of Gold Standard datasets for LLMs and improved reasoning reliability. I engineered supervised fine-tuning (SFT) workflows, converting unstructured research data into labeled formats. My efforts optimized feedback cycles and dataset usefulness for model training. • Developed and implemented quality assurance processes. • Engineered SFT using JSON/YAML schemas. • Reduced hallucination rates and improved model trustworthiness. • Coordinated human-in-the-loop (HITL) feedback for annotation.

2023 - 2024

AI Data Labeling and QA Lead

SamaTextFine-tuning

As AI Data Labeling and QA Lead at Sama, I directed large-scale labeling projects for high-stakes AI training data. I architected annotation rubrics and enforced strict safety and compliance protocols. I advanced failure-mode labeling and integrated peer-reviewed feedback into the annotation workflow. • Created standardized annotation protocols for dialogue data. • Systematized reasoning chain documentation for debugging. • Led a team focused on ambiguous or challenging data cases. • Bridged research and production for annotated datasets.

2022 - 2023

Data & AI Annotation specialist

TextClassification

As Data & AI Annotation specialist (Contract) at Microsoft, I validated and labeled massive AI/ML training datasets. I maintained high precision against evolving annotation guidelines, ensuring reliable data for downstream models. My work included detection and correction of labeling drift and nuanced edge cases. • Supported large-scale dataset validation initiatives. • Enhanced logical consistency across labeled training data. • Improved model robustness by documenting edge cases. • Collaborated on continuous improvement of annotation standards.

2019 - 2021

Education

Work History