Peter Unachukwu

Key Skills

Software

Telus

Appen

Scale AI

Other

Labelbox

Roboflow

Top Subject Matter

Nlp Domain Expertise

Multimodal Data Annotation

Rlhf Domain Expertise

Top Data Types

Text

Image

Top Task Types

RLHF

Bounding Box

Classification

Entity (NER) Classification

Freelancer Overview

Data Annotator & AI Trainer (Telus Digital). Brings 12+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Scale AI, Appen, and Labelbox. Education includes Master of Science, University of Lagos (2023) and Bachelor of Science, Nnamdi Azikiwe University (2020). AI-training focus includes data types such as Text and Image and labeling workflows including Entity (NER) Classification, Evaluation, and Rating.

Labeling Experience

Data Annotator & AI Trainer | Telus Digital

Scale AITextRLHFEntity Ner Classification

Annotated and labeled over 50,000+ data points across text, image, audio, and video modalities for AI/ML training with 98%+ accuracy. Performed pairwise comparisons and ranked AI-generated responses to support RLHF workflows, and evaluated natural language outputs for various quality metrics. Conducted entity tagging, sentiment labeling, intent classification, and named entity recognition for NLP model development. • Multilingual dataset expansion leveraging native Hausa proficiency. • Utilized annotation platforms like Scale AI, Appen, and Labelbox. • Collaborated with QA teams to ensure annotation consistency. • Provided failure pattern feedback to engineering teams for prompt improvements.

Annotated and labeled over 50,000+ data points across text, image, audio, and video modalities for AI/ML training with 98%+ accuracy. Performed pairwise comparisons and ranked AI-generated responses to support RLHF workflows, and evaluated natural language outputs for various quality metrics. Conducted entity tagging, sentiment labeling, intent classification, and named entity recognition for NLP model development. • Multilingual dataset expansion leveraging native Hausa proficiency. • Utilized annotation platforms like Scale AI, Appen, and Labelbox. • Collaborated with QA teams to ensure annotation consistency. • Provided failure pattern feedback to engineering teams for prompt improvements.

2022 - Present

AI Data Quality Analyst | Appen

AppenText

Reviewed and validated AI outputs for accuracy, relevance, and safety in search, voice, and generative AI projects. Performed linguistic quality checks and cross-lingual evaluations for Hausa and English datasets to benchmark model performance. Executed relevance ratings, taxonomy classification, and ontology development for knowledge graphs in e-commerce and healthcare.• Ranked in the top 10% of contributors for accuracy and efficiency.• Conducted query-result alignment assessments with detailed guidelines.• Enhanced low-resource language datasets for global technology clients.• Improved safety and performance of AI models through rigorous data review.

Reviewed and validated AI outputs for accuracy, relevance, and safety in search, voice, and generative AI projects. Performed linguistic quality checks and cross-lingual evaluations for Hausa and English datasets to benchmark model performance. Executed relevance ratings, taxonomy classification, and ontology development for knowledge graphs in e-commerce and healthcare.• Ranked in the top 10% of contributors for accuracy and efficiency.• Conducted query-result alignment assessments with detailed guidelines.• Enhanced low-resource language datasets for global technology clients.• Improved safety and performance of AI models through rigorous data review.

2023 - 2024

Machine Learning Data Contributor | Scale AI

Scale AIImageBounding Box

Contributed to large-scale RLHF and autonomous vehicle projects by annotating multimodal datasets including image-text pairs and performing bounding box labeling. Wrote gold-standard human responses used for next-generation LLMs and conducted keypoint detection for robotics. Evaluated AI model outputs using helpfulness, harmlessness, and honesty rubrics. • Earned 99.2% task acceptance on Scale AI platform. • Annnotated image, text, and bounding box data for multiple industries. • Employed rubrics for conversational AI output evaluation. • Trusted Contributor status on platform for high-quality work.

Contributed to large-scale RLHF and autonomous vehicle projects by annotating multimodal datasets including image-text pairs and performing bounding box labeling. Wrote gold-standard human responses used for next-generation LLMs and conducted keypoint detection for robotics. Evaluated AI model outputs using helpfulness, harmlessness, and honesty rubrics. • Earned 99.2% task acceptance on Scale AI platform. • Annnotated image, text, and bounding box data for multiple industries. • Employed rubrics for conversational AI output evaluation. • Trusted Contributor status on platform for high-quality work.

2022 - 2023

Freelance AI Data Specialist | Independent / Remote Clients

Scale AITextClassification

Delivered data collection, preprocessing, and annotation services for text classification and object detection projects for international AI firms. Built, cleaned, and curated labeled datasets from web-scraped and user-generated content, ensuring data quality for supervised models. Moderated content by labeling, flagging, or filtering harmful, biased, or policy-violating examples to support trust and safety standards.• Developed quality assurance workflows for annotation verification.• Maintained high inter-annotator agreement and consistency scores.• Focused on trust and safety labeling for NLP datasets.• Provided annotations for client projects on a freelance basis.

Delivered data collection, preprocessing, and annotation services for text classification and object detection projects for international AI firms. Built, cleaned, and curated labeled datasets from web-scraped and user-generated content, ensuring data quality for supervised models. Moderated content by labeling, flagging, or filtering harmful, biased, or policy-violating examples to support trust and safety standards.• Developed quality assurance workflows for annotation verification.• Maintained high inter-annotator agreement and consistency scores.• Focused on trust and safety labeling for NLP datasets.• Provided annotations for client projects on a freelance basis.

2021 - 2022

Education

Work History