Carnegie Mellon University

How this program compares

Budget-wise, $80.4K puts this master's program at the 88th percentile on cost — about 87% above the $42.9K average across 394 comparable listings. It runs on a full-time schedule (on-campus).

Admission Snapshot

Typical admitted student: Requires a bachelor's degree in engineering, computer science, or a related technical field with a minimum GPA of 3.0, strong quantitative background including calculus and linear algebra, and programming experience; GRE is optional but recommended for competitive applicants.

About This Program

This interdisciplinary degree combines artificial intelligence fundamentals with innovation management to prepare STEM professionals for technology leadership roles. Coursework concentrates on Machine Learning and Deep Learning. Most students complete it in about 1.5 years.

Design and deploy scalable AI models for real-world engineering applications.

Estimated total tuition is $80.4K, above the $42.9K average for AI master's programs in our database and in the 88th percentile on cost at this level. Applicants should weigh that premium against the program's outcomes and brand.

It is one of 60 AI-related programs we track in Pennsylvania, of which about 43% offer an online option. On price, it comes in higher than about 59% of the Pennsylvania programs in our data, where typical tuition runs near $81.1K.

Graduates frequently move into roles such as Product Analyst, with reported salaries around $145,000.

Career Outcomes

The MS in AI Engineering (ETIM Track) at Carnegie Mellon University (Pittsburgh, Pennsylvania) is oriented toward Product Analyst hiring, with alumni reporting pay near $145,000. Its focus on Machine Learning and Deep Learning maps directly to how employers in business ai screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 32% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. AI Engineer
• 2. Machine Learning Engineer
• 3. AI Systems Architect
• 4. Technology Innovation Manager

What You'll Learn

• Design and deploy scalable AI models for real-world engineering applications
• Optimize machine learning systems for performance and efficiency
• Integrate AI technologies into engineering workflows and products
• Apply engineering principles to AI ethics, reliability, and innovation management

Curriculum Highlights

The structure includes core engineering innovation courses, artificial intelligence fundamentals, a capstone project, and a professional internship.

Top Employers

Top employers include Google, Meta, Amazon, NVIDIA, and tech consultancies like McKinsey Digital.

Admissions

Admission to Carnegie Mellon University's MS in AI Engineering (ETIM Track) generally expects a bachelor's degree. The GRE is optional here — a growing norm among AI programs — so applicants can often lead with coursework, projects and recommendations instead. Deadlines, testing policies and funding change year to year, so confirm the current requirements on the official program page before applying.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 3
• Resume: Required
• Transcripts: Official transcripts required

Frequently Asked Questions