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Remote Mechanical Engineering ProfessorMicro1 • Dunn Loring, Virginia, US
Remote Mechanical Engineering Professor

Remote Mechanical Engineering Professor

Micro1 • Dunn Loring, Virginia, US
11 days ago
Salary
$60.00 hourly
Job type
  • Full-time
  • Remote
Job description
Mechanical Engineering Professor$60 - $130/hourpay

Required Skills

mechanical engineeringsolid and structural mechanicsdynamics and vibration and controlthermal-fluidstechnical writingassessment designeducational content creationwritten communicationverbal communicationattention to detailtechnical accuracyremote collaborationself-motivationorganizationdigital workflow tools

About micro1

micro1 is the leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms that real-world expertise into high-quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.

Our platform identifies and vets top talent through an AI recruiter, enabling high-quality expert contributions at scale. We aim to enable 1 billion people to do meaningful work by applying their expertise to AI. As our global expert network grows, micro1 is building the human intelligence layer for frontier AI.

Role Title: Mechanical Engineering Professor


Role Type: Contractor


Location: Remote


micro1 is engaging Mechanical Engineering Professors, adjuncts, and academic instructors to participate in a high-impact AI research project for a customer. 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

  1. Design and author rigorous single-option (multiple-choice) assessment questions in your specialization within mechanical engineering, calibrated for graduate or postgraduate complexity.
  2. Translate advanced concepts from Solid & Structural Mechanics, Dynamics & Vibration & Control, or Thermal-Fluids into challenging exam-quality content.
  3. Develop detailed explanations and rationales for answer choices, maintaining the clarity and precision expected in academic settings.
  4. Review and validate the technical accuracy and pedagogical quality of AI-generated mechanical engineering materials.
  5. Collaborate asynchronously with other subject matter experts and project coordinators to refine and improve content quality.
  6. Conduct quality checks, revisions, and enhancements on contributed materials based on feedback and project standards.
  7. Maintain thorough records of assignments and submissions using digital workflow tools provided for the engagement.


Preferred Qualifications

  1. PhD or MS in Mechanical Engineering, with current or previous university-level teaching experience (professor, adjunct, lecturer, or TA) in one or more core areas: Solid & Structural Mechanics, Dynamics & Vibration & Control, or Thermal-Fluids.
  2. Experience authoring, grading, or reviewing graduate-level exams, problem sets, or coursework.
  3. Demonstrated ability to convert complex mechanical engineering principles into clear, exam-ready written content.
  4. Background in assessment design, rubric development, or educational content creation.
  5. Exceptional written and verbal communication skills; adept at articulating intricate concepts concisely and accurately.
  6. Meticulous attention to detail and commitment to technical accuracy in all deliverables.
  7. Self-motivated, organized, and comfortable working independently in a remote, asynchronous project environment; familiarity with collaborative digital platforms is a plus.


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.

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Remote Mechanical Engineering Professor • Dunn Loring, Virginia, US

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