Joel - Lead AI Training & Data Annotation Specialist

Demonstrated experience with AI Training.

Demonstrated experience with Data Annotation.

Demonstrated experience with Multimodal Annotation.

Demonstrated experience with Model Evaluation.

Demonstrated experience with Quality Assurance.

Applied approximately 4 years of AI training and annotation experience across 4 modalities—text, audio, image, and video—for machine-learning, NLP, and computer-vision workflows.. Supported prompt-engineering and AI-output review workflows, assessing generated content for comprehension, clarity, and overall output quality within project requirements.. Developed and applied annotation guidelines and QA protocols to improve labeling consistency, data integrity, and dataset readiness for model-development workflows.. Performed model and output quality reviews, identifying annotation issues, inconsistencies, and edge cases requiring correction or clarification.. Worked across 3 named annotation platforms—SuperAnnotate, Label Studio, and Appen—to execute and manage structured annotation workflows.. Maintained detailed documentation of annotation decisions and workflow requirements to support consistent application of project guidelines.

Applied 2 years of content-creation and visual communication experience to produce cross-modal content and shot-by-shot descriptions for video and image projects.. Developed prompts for AI-powered content-creation tools and translated complex concepts into precise visual instructions.. Collaborated with marketing teams to maintain accuracy, clarity, consistency, and alignment with project requirements.