University of Washington

How this program compares

Benchmark this program against our national recognition pages and use the key guides below to evaluate ROI, admissions difficulty, and outcomes.

Admission Snapshot

Typical admitted student: A bachelor's degree in engineering, computer science, or a related STEM field with a minimum GPA of 3.0 is required, along with programming experience and quantitative coursework in linear algebra, calculus, and statistics.

About This Program

This master's program enables engineers to leverage AI and machine learning tools to solve complex technical challenges across diverse engineering disciplines.

Career Outcomes

Position as Machine Learning Engineer in Engineering AI with machine learning expertise

• 1. Machine Learning Engineer
• 2. AI Systems Engineer
• 3. Data Science Engineer
• 4. AI Research Engineer

What You'll Learn

• Implement machine learning models for engineering problems
• Apply deep learning techniques to real-world data
• Design AI systems integrating algorithms and data processing
• Evaluate ethical and societal impacts of AI in engineering

Curriculum Highlights

The structure includes core AI and machine learning coursework combined with discipline-specific modules like dynamic systems and systems operations.

Top Employers

Top employers include tech giants like Amazon, Microsoft, Google, and engineering firms such as Boeing and Lockheed Martin.

Admissions

A bachelor's degree in engineering, computer science, or a related STEM field with a minimum GPA of 3.0 is required, along with programming experience and quantitative coursework in linear algebra, calculus, and statistics.

Application Materials

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

Academic Requirements

• Degree Required: Bachelor's degree
• GRE/GMAT: Optional
• TOEFL/IELTS: Required for international students (TOEFL 92+ / IELTS 7.0+)