Senior 3D NAND TCAD Modeling Engineer

Solidigm; California (MO); Hybrid; USD 159,000 - 255,000; Full time

Benefits offered by this job

RSU program

RCU program

Cash bonus

Job summary

Solidigm is seeking a TCAD Modeling Engineer to build predictive 3D NAND and CMOS TCAD models, collaborating across organizations to drive insights and solutions. The role focuses on computational geometry, physics-based simulations, and data-driven validation to overcome scaling challenges in NAND devices.

You will work with cross-functional teams, design DOE, and contribute to model deployment while applying deep semiconductor physics knowledge. Hybrid work is available, with travel as needed.

Qualifications

• BS, MS, or PhD in a related science or engineering discipline.
• 5–10 years of proven TCAD modeling experience in relevant technical areas.
• In-depth knowledge of semiconductor physics and scaling principles.
• Must understand NAND device physics.
• Proficient with Synopsys process and device simulator tool suite.
• Experience in computational geometry and structure modeling.
• Strong communication and collaboration skills.

Responsibilities

• Develops and codes software programs, algorithms, and computational modeling tools.
• Develops methods for predictive TCAD simulations across NAND technology nodes.
• Collaborates with PI and process teams for model development & deployment; designs DOE.
• Analyzes E-test data, interprets experiments, and presents insights to engineering teams.

Skills

TCAD modeling

Semiconductor physics

Data analysis

Cross-functional collaboration

Education

BS/MS/PhD in related field

Tools

Synopsys TCAD tools

Job description

Solidigm is seeking a TCAD Modeling Engineer to build predictive 3D NAND and CMOS TCAD models, collaborating across organizations to drive insights and solutions. The role focuses on computational geometry, physics-based simulations, and data-driven validation to overcome scaling challenges in NAND devices.

You will work with cross-functional teams, design DOE, and contribute to model deployment while applying deep semiconductor physics knowledge. Hybrid work is available, with travel as needed.