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Cypress HCM is seeking a Content & Experience Evaluator in Los Angeles to join the Member Experience team. You will assess films, series, and related content to train and improve AI-driven member experiences, providing nuanced judgments and clear annotations.
The role requires deep knowledge of visual media, fluency in English, strong writing, and the ability to work with large datasets and internal tools. Spanish is a strong plus for this role.
The Opportunity If you're an avid fan and serious expert in visual entertainment, the Member Experience team is seeking a unique candidate who can capture the essence of films, series, and other content, all while keeping the experience of our users top of mind.
Content & Experience Evaluator, 3335-1 Member Experience The Opportunity If you're an avid fan and serious expert in visual entertainment, the Member Experience team is seeking a unique candidate who can capture the essence of films, series, and other content, all while keeping the experience of our users top of mind. As a Content & Experience Evaluator, your work will directly contribute to the training, evaluation, and improvement of GenAI applications that power member-facing experiences. In this role, you'll apply expert judgment to rate, annotate, and review large-scale content datasets used to train and refine AI systems. By bringing nuance, consistency, and clarity to content evaluation, you'll help ensure that AI-driven solutions better understand films and series, respond accurately to member needs, and deliver high-quality, trusted experiences at scale.
Has a deep and broad knowledge of visual media and is passionate about global entertainment, with a strong understanding of films and series across genres and markets. They can succinctly and objectively communicate what is important about a piece of content, and why, distilling complex creative works into clear, structured insights. The ideal candidate is experienced as an expert annotator, rater, or dataset reviewer, particularly in structured or rubric-based environments that support AI or machine-learning use cases. They are comfortable applying expert judgment within defined frameworks, navigating nuance and ambiguity while maintaining consistency and quality at scale. They thrive in a high-volume, high-quality, deadline- and data-driven environment, and are highly detail-oriented, reliable, and disciplined in their work. They are flexible, adaptive, and curious, with the ability to evolve alongside changing tools, processes, and organizational needs, and are motivated by work that directly improves member-facing experiences through high-quality data.