AI Foundations Subject Matter Expert

DescriptionRole OverviewEase Learning is seeking a qualified Subject Matter Expert (SME) with applied, real-world experience in AI Foundations to participate in a skills assessment validation engagement. This is a short-term, contract, remote engagement in which the SME will complete a practitioner-level skills assessment and a brief post-assessment survey. This role does not involve teaching, instructional design, content creation, or ongoing advisory responsibilities.Engagement DetailsEngagement Type: Contract / 1099 – Short-term engagementLocation: RemoteEstimated Item Count: ~150Estimated Time to Completion: Approximately 1–2 hoursAssessment Window: Work must be completed within a defined access window (typically 5 business days once access is granted)Scope of WorkComplete a practitioner-level skills assessment used for validation and standard-setting purposes.Complete a short post-assessment survey providing feedback on the assessment experience.This Role Does Not IncludeTeaching or facilitation responsibilitiesInstructional or curriculum design workContent authoring or SME review of materialsOngoing advisory or consulting responsibilitiesRequirementsRequired ExpertiseThe SME should be a current practitioner with applied, real-world experience related to the following knowledge areas and skills:Define artificial intelligence and describe its core concepts and capabilitiesExplain how AI systems learn from data, including supervised, unsupervised, and reinforcement learningDescribe how generative AI produces new text, images, and other contentUnderstand the architectures and techniques that enable AI systems to interpret data and automate decisionsIdentify common AI frameworks, models, and tools used in practiceExplain the role of data quality, scale, and bias in training AI modelsDescribe the impact of training data on AI model performance and reliabilityUnderstand the operational aspects of deploying and managing AI systems in real-world settingsExplain foundational concepts of neural networks and deep learningDescribe natural language processing (NLP) and computer vision fundamentalsIdentify ethical considerations and responsible AI principlesUnderstand the difference between narrow AI and general AI conceptsDescribe real-world applications of AI across industriesEvaluate AI solutions for practical business and technical use casesIdeal Candidate ProfileActive practitioner with hands-on experience in AI Foundations or closely related domains.Practical, working knowledge of how the concepts listed above are applied in real professional settings.Does not need to be an academic researcher or industry thought leader — applied experience is what matters.Minimum Performance ExpectationParticipants must demonstrate baseline practitioner competency by scoring above 50% on the assessment. This threshold is used solely to ensure valid practitioner-level participation and is not used for hiring, ranking, or performance evaluation.DeliverablesCompleted skills assessment within the defined access window.Completed post-assessment survey.CompensationThis is a flat-fee engagement, paid upon successful completion of the assessment and survey.