Role Overview

Ease 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 Details

Engagement Type: Contract / 1099 – Short-term engagement

Location: Remote

Estimated Item Count: ~150

Estimated Time to Completion: Approximately 1–2 hours

Assessment Window: Work must be completed within a defined access window (typically 5 business days once access is granted)

Scope of Work

• Complete 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 include:

• Teaching or facilitation responsibilities
• Instructional or curriculum design work
• Content authoring or SME review of materials
• Ongoing advisory or consulting responsibilities

Required Expertise

The 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 capabilities
• Explain how AI systems learn from data, including supervised, unsupervised, and reinforcement learning
• Describe how generative AI produces new text, images, and other content
• Understand the architectures and techniques that enable AI systems to interpret data and automate decisions
• Identify common AI frameworks, models, and tools used in practice
• Explain the role of data quality, scale, and bias in training AI models
• Describe the impact of training data on AI model performance and reliability
• Understand the operational aspects of deploying and managing AI systems in real-world settings
• Explain foundational concepts of neural networks and deep learning
• Describe natural language processing (NLP) and computer vision fundamentals
• Identify ethical considerations and responsible AI principles
• Understand the difference between narrow AI and general AI concepts
• Describe real-world applications of AI across industries
• Evaluate AI solutions for practical business and technical use cases

Ideal Candidate Profile

• Active 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 Expectation

Participants 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.

Deliverables

• Completed skills assessment within the defined access window.
• Completed post-assessment survey.

Compensation

This is a flat-fee engagement, paid upon successful completion of the assessment and survey.