Daniel Burton

Led a team of seven on Meta MediaGenGenAI Support Services, supporting client AI projects through data training, annotation, and evaluation. Analyzed team statistics, coordinated meetings and time-off decisions, and provided quality feedback on model responses.

Served as an operational bridge between enterprise clients, internal stakeholders, and a talent network of up to 2,500 agents to deliver large-scale AI optimization projects. Built data-driven insights using real-time analytics to audit performance, identify workflow inefficiencies, and mitigate risks such as time theft and non-work for a team of up to 100.

Annotated game content including dialogues, quests, and character interactions while ensuring accuracy and consistency to optimize player experience. Reviewed rater tasks for guideline adherence and evaluated model responses against evaluation rubrics to improve dialogue quality and interactions.

Accurately labeled and audited complex multi-modal datasets (text, image, audio, video) according to detailed project guidelines. Collaborated with ML engineers and project leads to refine taxonomy, annotation protocols, and edge-case definitions, and escalated issues for clarification.

Annotated AI datasets to improve algorithm accuracy and enhance model performance using measurable results. Implemented detailed annotation guidelines to maintain consistent, accurate labeling while analyzing and categorizing large volumes of data.

Diploma of Technology in Business Information Technology Management (Artificial Intelligence Management) at BCIT.

Grade: Merit

Completed a Level 5 ESL Diploma with a Merit pass.

Completed education at Belmont Senior Secondary in Victoria, Canada.