David B.

Key Skills

Software

AWS SageMaker

Appen

Axiom AI

Clickworker

CloudFactory

CrowdSource

CVAT

Dataloop

iMerit

Labelbox

OneForma

Remotasks

Snorkel AI

SuperAnnotate

Telus

Scale AI

Don't disclose

Top Subject Matter

Self Driving Car Imagery

LLM in English, Working with text data for sentiment analysis, language translation, chatbots, and other language-based AI applications.

Data Annotation and Labeling

Top Data Types

Image

Text

Video

Audio

Document

Top Task Types

Bounding Box

Classification

Data Collection

Evaluation/Rating

Mapping

Entity (NER) Classification

Freelancer Overview

CEO & Founder, Rater-X (Human-in-the-Loop evaluation infrastructure). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Don't disclose. AI-training focus includes data types such as Audio, Text, and Image and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

CEO & Founder, Rater-X (Human-in-the-Loop evaluation infrastructure)

Audio

Built a human-in-the-loop AI evaluation framework at scale for trusted AI systems. Oversaw evaluator calibration and inter-rater agreement to ensure consistent, objective judgments across distributed teams. Translated complex evaluation guidelines into actionable workflows for multilingual and multimodal assessments. • Designed evaluation rubrics and quality frameworks for text and multimodal tasks, including naturalness scoring and dialect classification. • Recruited and trained evaluators while establishing calibration systems to maintain consistency. • Coordinated cross-functional teams to deliver reliable evaluation pipelines. • Partnered with AI companies and data organizations to improve model training data quality.

2024 - Present

AI Data Contributor, Welocalize / Welo Data

Don't discloseAudio

Performed language and content evaluation aligned with Welo Data project rubrics and quality standards. Assessed speech naturalness, content accuracy, and dialectal appropriateness for multilingual evaluation assignments. Applied consistent rubric-based judgments to support reliable evaluation outputs. • Rated speech naturalness across diverse audio evaluation tasks. • Checked content accuracy and alignment to expected meaning. • Evaluated dialectal appropriateness using regional language knowledge. • Followed standardized rubrics and quality criteria for submissions.

2025 - 2026

Data Quality Analyst, Cohere

Don't discloseText

Validated AI model outputs for accuracy, relevance, and policy compliance across large-scale evaluation workflows. Applied consistent rubric-based judgment to assess policy-sensitive edge cases affecting user trust. Supported reliability improvements through root-cause analysis and collaboration with engineering teams. • Evaluated accuracy, relevance, and policy compliance for LLM outputs. • Conducted root-cause analysis on data and model quality failures. • Partnered with engineering to resolve model performance issues. • Maintained inter-rater agreement and consistency across enterprise workflows.

2025 - 2025

Online Data Analyst, Peroptyx

Don't discloseTextClassification

Performed search relevance and query intent evaluation for AI-driven search and recommendation systems. Assessed annotation task data quality by identifying trends and anomalies that impacted model decision-making accuracy. Applied objective, guideline-based judgment to produce consistent evaluation results. • Classified query intent using language and user behavior patterns. • Rated relevance to improve ranking and recommendation quality. • Identified anomalies and quality issues to enhance downstream decisions. • Followed complex evaluation guidelines to ensure consistency.

2023 - 2024

Data Annotator, Telus International

Don't discloseTextEntity (NER) Classification

Completed NLP annotation work to support AI model training initiatives. Conducted sentiment analysis and applied text and image tagging for dataset creation. Maintained dataset integrity by following consistency and quality requirements across large-scale multi-annotator projects. • Labeled text for NLP features to support machine learning training. • Performed sentiment analysis for annotated datasets. • Tagged text and images to create validated ML datasets. • Monitored annotation progress and ensured accuracy in multi-annotator runs.

2021 - 2023

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Education

Work History