Samuel E.

Key Skills

Software

Scale AI

Toloka

Appen

Top Subject Matter

AI/ML training data for Japanese-English NLP

search quality

and computer vision/NLP multimodal projects

Top Data Types

Text

Image

Document

Top Task Types

Classification

Red Teaming

Freelancer Overview

Senior Data Annotation Specialist (Contracted Remote Annotator) at Scale AI. Brings 13+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Scale AI, Toloka, and Appen. Education includes Master of Science, University of Manchester (2015) and Bachelor of Science, University of Leeds (2013). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Senior Data Annotation Specialist (Contracted Remote Annotator) at Scale AI

Scale AIText

Led Japanese and multilingual NLP annotation workflows for high-complexity client datasets, ensuring guideline compliance and high labeling consistency across runs. Completed large-scale text tasks including NER, coreference resolution, semantic role labeling, and search quality evaluation while maintaining strong acceptance rates. Performed rigorous QA checks to preserve label accuracy and improve model performance over iterative project cycles. • Maintained Top 2% global performance on Scale AI with high quality acceptance. • Developed and applied Japanese annotation consistency practices to reduce disagreement. • Supported premium Japanese language tasks including JLPT-level text evaluation. • Produced linguistically validated outputs for Japanese language datasets.

2021 - Present

Data Annotation & Linguistic Quality Specialist at Toloka (Yandex)

TolokaTextClassification

Served as an independent contractor annotating and linguistically validating Japanese and English datasets for AI training and research. Completed large volumes of linguistic labeling and evaluation tasks for NLP, speech-related labeling, and conversational AI. Maintained gold-standard quality benchmarks and contributed to dataset improvement through consistent guideline adherence. • Completed 180,000+ tasks on Toloka with 98.4% aggregate quality score. • Labeled intent/entity information for chatbot training conversations. • Performed search relevance rating using strict RATER guidelines. • Provided phonetic-accuracy validation for Japanese audio transcription labels.

2019 - Present

AI Training Data Annotator at Appen

AppenText

Contributed to AI training dataset labeling as a crowd worker and project contributor, completing text and multimodal annotation assignments based on project guidelines. Performed sentiment and text relevance labeling and supported audio transcription tasks to support downstream model training. Completed tasks with consistently high aggregate quality scores aligned to platform qualification standards. • Completed 180,000+ text and audio-related tasks including sentiment labeling. • Produced image classification and text relevance ratings for AI training. • Performed audio transcription labeling for speech-based models. • Maintained Gold Standard qualification across multiple project types.

2018 - 2020

Content Moderator & Text Annotation Analyst at Lionbridge AI (now Telus International AI)

TextRed Teaming

Performed content moderation and text annotation duties for AI training and policy compliance datasets. Evaluated user-generated content against safety and policy guidelines while producing structured annotations for downstream moderation models. Ensured accurate labeling and consistent application of rule-based criteria across platform content. • Moderated social media and e-commerce user-generated content. • Provided policy compliance annotations for safety-oriented labeling tasks. • Supported text annotation for model training and quality improvement. • Worked under strict guidelines to maintain labeling accuracy.

2017 - 2018

Education

Work History