About the role
Role Title: Electrical Engineering Professor
Role Type: Contractor.
Location: Remote
micro1 is engaging Electrical Engineering Professors to contribute expertise to a high-impact project advancing AI research and assessment technology. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
Design and author graduate-level single-option (multiple-choice) exam questions within your area of electrical engineering specialization, ensuring rigor and authenticity.
Develop detailed explanations and precise grading rubrics for each question, consistent with academic standards and best practices in assessment.
Review and validate the technical accuracy and pedagogical strength of AI-generated content related to electrical engineering concepts.
Collaborate asynchronously with other subject matter experts to refine question quality, ensuring clarity, relevance, and academic rigor.
Evaluate AI model outputs, providing nuanced feedback that reflects your understanding of where models meet or diverge from human reasoning.
Clearly communicate complex technical concepts in written form, as for exam solutions or instructional content.
Contribute to a continually evolving, high-quality question bank that reflects advanced engineering reasoning.
Preferred Qualifications
PhD or advanced Master's degree in Electrical Engineering with demonstrated teaching experience at the university level (professor, adjunct, lecturer, or TA).
Experience authoring or reviewing graduate-level assessments, exams, or coursework in electrical engineering.
Deep subject matter knowledge in one or more of: Analog Circuits, Digital Circuits, RF, Power Electronics, with emphasis on Integrated Circuits (IC).
Expertise in rubric design, assessment development, or educational content creation.
Exceptional written communication skills, with a strong emphasis on clarity and academic rigor.
Demonstrated capacity to work independently, meet project milestones, and deliver high-quality contributions remotely.
Comfort with asynchronous collaboration on remote research or content development projects.
Compensation Structure
Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
Start Timeline & Availability
We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.
Originally posted on Himalayas