Position: Micro-Credential Grader-AI Fundamentals for STEM Professionals
Location: Fully remote (U.S.-based applicants only, no visa sponsorships)
Division: Rabb School of Continuing Studies, Brandeis University
Type: Part-Time, 4 months, varying hours, no more than 25 hours per week
Compensation: Hourly $25-$30
Reports to: Assistant Dean of Education and Learning Innovation
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.
What You Will Do:
- 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
What You Bring:
- 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.
Pay Range Disclosure
The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.
Equal Opportunity Statement