Boniface N.

Key Skills

Software

Scale AI

Remotasks

Toloka

CloudFactory

Top Subject Matter

Nlp Domain Expertise

conversational AI

and multimodal AI data labeling (text and audio transcripts)

Top Data Types

Text

Image

Document

Top Task Types

RLHF

Text Summarization

Red Teaming

Fine-tuning

Freelancer Overview

Electrical & Electronic Engineer (B.Eng., CGPA 4.37/5.0) with hands-on experience in AI data annotation, prompt engineering, and model evaluation across multiple platforms including Scale AI, Remotasks, and Toloka. Contributed to the labeling and curation of 15,000+ data samples spanning text, NLP, and conversational AI domains, and authored over 2,000 high-quality prompts for large language model fine-tuning. Proficient in RLHF workflows — ranking and rating AI-generated responses for helpfulness, harmlessness, and honesty — with a consistent 97%+ inter-annotator agreement rate. What sets me apart is a rare combination of deep technical literacy and strong written communication. My background in cybersecurity (CompTIA Security+, ISC² Scholar) sharpens my ability to identify adversarial inputs, safety violations, and edge cases in AI outputs — skills critical for red-teaming and safety alignment work. I have authored annotation guidelines, flagged policy-violating content, and collaborated asynchronously with distributed teams to meet quality benchmarks at scale. Recognized as a UN World Youth Summit delegate and multi-scholarship recipient, I bring both intellectual rigor and a commitment to responsible, high-impact AI development.

Labeling Experience

AI Data Trainer & Annotation Contributor (Freelance / Contract)

Scale AITextRLHF

Trained and annotated large volumes of supervised ML data for NLP and conversational AI, including text, audio transcripts, and structured inputs. Performed RLHF activities by ranking and rating model responses using the HHH (helpfulness, honesty, harmlessness) framework. Ensured outputs met instruction-following and safety requirements through continuous quality checks and policy compliance enforcement. • Labeled 15,000+ samples for supervised model training across NLP and conversational domains. • Rated/ranked responses for helpfulness, accuracy, harmlessness, and honesty under RLHF workflows. • Flagged edge cases, adversarial inputs, and policy-violating content to support red-teaming and safety alignment. • Achieved 97%+ inter-annotator agreement via consistent guidelines and quality assurance processes.

2023 - Present

Remote Penetration Tester & Beta Tester (AI Data Annotation & Labeling; Prompt Engineering & RLHF; Instruction-Following QA)

Text

Completed remote beta and penetration-testing activities focused on identifying and reporting software issues. Produced structured documentation describing findings, enabling more rigorous evaluation habits aligned with dataset and model quality review. Applied systematic analytical thinking that supports instruction-following QA and content safety validation practices. • Reduced critical web application vulnerabilities by 45% through continuous threat analysis and structured reporting. • Authored detailed technical test reports and bug documentation. • Conducted systematic software testing cycles and contributed to performance improvements. • Strengthened precision writing and analytical processes relevant to model output evaluation.

2022 - 2023

Education

Work History