Micro-Credential Grader-AI Fundamentals for STEM Professionals Job at Brandeis University

Job Description

Brandeis University’s Rabb School of Continuing Studies is seeking a detail-oriented STEM professional to serve as a Micro-Credential Grader for the online asynchronous credential, AI Fundamentals for STEM Professionals. In this fully remote, short-term hourly position, you’ll evaluate learner submissions that demonstrate mastery of AI concepts through a real-world STEM challenge and a complete 5-step workflow design. This project-based credential equips professionals with foundational skills in supervised learning, data preprocessing, model selection, and ethical AI deployment. As a grader, you’ll apply structured rubrics to assess technical accuracy, conceptual depth, and responsible innovation. This role offers a unique opportunity to contribute to a high-impact, workforce-aligned credential that bridges STEM expertise with emerging AI capabilities.

Job Responsibility

Evaluate learner submissions of the AI Workflow Project, which include a real-world STEM challenge, an AI-powered solution, and a complete 5-step workflow design
Apply structured rubrics to assess mastery of skills such as supervised learning, data preprocessing, model selection, and interpretability
Participate in calibration exercises with fellow graders (if needed) to ensure consistency in evaluating technical artifacts and conceptual reasoning
Maintain confidentiality and objectivity throughout the grading process

Requirements

Bachelor’s degree required
Master’s degree preferred in Computer Science, Data Science, Engineering, or related STEM disciplines
Subject-matter expertise in foundational AI concepts, including machine learning, data analysis, and ethical considerations in AI deployment
Experience in academic assessment, workforce development, or digital learning preferred
Familiarity with learning management systems (Moodle preferred), online credentialing platforms, and collaborative grading workflows
Professional, learner-centered approach with a commitment to academic integrity and continuous improvement
Proficient in rubric-based assessment and competency validation, especially for technical and project-based submissions
Strong attention to detail and ability to maintain consistency across diverse submissions
Excellent written communication skills for delivering constructive, learner-focused feedback
Comfortable working in asynchronous learning environments and using digital platforms
Adaptability in managing multiple grading tasks within deadlines

Nice to have

Experience in academic assessment, workforce development, or digital learning preferred
Familiarity with learning management systems (Moodle preferred), online credentialing platforms, and collaborative grading workflows

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Micro-Credential Grader-AI Fundamentals for STEM Professionals

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