Staff GenAI Engineer — AI-Driven Memory Design & Automation

Micron Technology, Inc.; San Jose, Northern (CA, KY); Hybrid; USD 170,000 - 290,000; Full time

Benefits offered by this job

Medical, dental and vision plans

Paid time off

Paid holidays

Equity

Job summary

Micron Technology, Inc. is seeking a Staff GenAI Engineer in San Jose to embed AI into design, layout, verification, and CAD workflows.

You will drive AI-assisted optimization and data-driven improvements across memory design, tapeout cycles, and silicon outcomes with cross-functional teams. The ideal candidate has 5–7 years in circuit design/verification, strong Python coding, and experience applying ML to engineering workflows.

Qualifications

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent practical experience.
• 5–7 years experience with circuit design, layout, verification, or CAD flows.
• Strong coding skills in Python or similar languages.
• Experience applying data analysis, machine learning, or automation to engineering workflows.

Responsibilities

• Embed AI and automation into circuit design, layout, and verification workflows.
• Apply data-driven methods to modeling, validation, and tape-out iteration reduction.
• Enable AI-assisted optimization of floorplanning, placement, routing, and simulation.
• Leverage historical design and silicon data to drive predictive insights.
• Collaborate across design, CAD, and manufacturing teams to scale AI-enabled methods.

Skills

Circuit design

Layout

Verification

CAD flows

Python

Data analysis

Machine learning

Education

Bachelor’s degree

Master’s degree or PhD preferred

Job description

Micron Technology, Inc. is seeking a Staff GenAI Engineer in San Jose to embed AI into design, layout, verification, and CAD workflows.

You will drive AI-assisted optimization and data-driven improvements across memory design, tapeout cycles, and silicon outcomes with cross-functional teams. The ideal candidate has 5–7 years in circuit design/verification, strong Python coding, and experience applying ML to engineering workflows.