Course Instructor- Generative AI for Engineers

CMU group; Pittsburgh (Allegheny County); On-site; USD 55,000 - 83,000; Part time

Job summary

Carnegie Mellon University—College of Engineering, Mechanical Engineering, in Pittsburgh, PA, seeks an adjunct instructor to develop and teach a course on Generative AI for Engineering Applications.

The successful candidate will bring expertise in machine learning, computational modeling, or AI-enabled engineering systems to design and deliver instruction focused on building, adapting, and applying generative models for mechanical engineering problems.

Qualifications

• Experience in machine learning, computational modeling, or AI-enabled engineering systems to design and deliver instruction on generative models.

Responsibilities

• Develop and teach a course on Generative AI for Engineering Applications.
• Design curriculum, content, and assessments.
• Record high-quality asynchronous lectures and develop instructional materials.
• Facilitate project-based learning and evaluate student work.
• Teach all scheduled sessions and perform instructional/administrative duties.

Skills

Machine learning

Computational modeling

Generative models

Python

PyTorch

AI-enabled engineering systems

Tools

Python

PyTorch

Job description

Carnegie Mellon University: College of Engineering: Mechanical Engineering

Location

Carnegie Mellon University: College of Engineering: Mechanical Engineering, Pittsburgh, PA

Open Date

Jul 17, 2026

Description

The Department of Mechanical Engineering seeks an adjunct Instructor to develop and teach a course on Generative AI for Engineering Applications. The successful candidate will bring expertise in machine learning, computational modeling, or AI-enabled engineering systems to design and deliver instruction focused on building, adapting, and applying generative models for mechanical engineering problems.

This role emphasizes core course development, including curriculum design, technical content creation, and assessment development. Instruction will cover foundational generative architectures such as transformers, diffusion models, and neural operators, with applications in geometry generation, surrogate modeling, materials and microstructure design, and simulation workflows. The instructor will develop hands‑on assignments, guided projects, and assessments using Python and PyTorch and real‑world engineering datasets.

The instructor will also be responsible for recording high‑quality asynchronous lecture videos, developing supporting instructional materials, and ensuring alignment between learning objectives, assessments, and course outcomes. In addition, the instructor will facilitate project‑based learning and evaluate student performance through technical assignments and project deliverables.

The instructor will teach all scheduled sessions listed on the Mechanical Engineering academic calendar and complete associated instructional and administrative duties. The expected time commitment is approximately 10 hours per week for the duration of the course.

Carnegie Mellon Universityis an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information. Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders.