Staff STPG NAND Product Development Engineer

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Micron Technology, Inc. is seeking a Staff Engineer in the System and Technology Product Group to own the full learning loop for NAND TCV development, driving pre-silicon validation, post-silicon characterization, and silicon learning to influence architectures and test strategies.

The role requires strong technical judgment, advanced data analysis, and cross-functional collaboration, with the ability to independently resolve complex issues and mentor engineers across teams.

Qualifications

• PhD with ≥2 years, or Master’s with ≥5 years, or Bachelor’s with ≥7 years of relevant experience in Electrical Engineering, Materials Science, Chemical Engineering, Physics, or a related field, with demonstrated expertise in semiconductor industry.
• Demonstrated experience in both pre-silicon simulation/regression ownership and post-silicon validation for complex semiconductor designs.
• Experience driving technical problem resolution with a high degree of independence.

Responsibilities

• Own pre-silicon validation, simulation coverage, regression development, and correlation activities for TCV programs.
• Analyze simulation results to identify architecture, device, performance, and margin sensitivities that influence tape-out readiness.
• Own post-silicon validation, characterization, debug, and silicon learning activities for TCV devices.
• Drive root cause analysis of silicon anomalies and distinguish design, process, modeling, and test-related limitations.
• Define test modes, patterns, stress conditions, and characterization methodologies to maximize technology learning and data quality.
• Lead data-driven problem solving and influence cross-functional decisions through technical expertise and execution.
• Collaborate with Design, Technology Development, Process Integration, and Test organizations to accelerate technology learning.
• Partner with Test Solutions Engineering to influence probe code, test flows, and characterization strategies.
• Develop technical documentation, best practices, and reusable methodologies that improve organizational learning.
• Mentor less-experienced engineers and promote knowledge sharing across teams.

Skills

CMOS device physics

NAND flash architectures

Semiconductor devices

Data analysis

Python scripting

Statistical evaluation

DFT

Probe test infrastructure

Machine learning / AI techniques

Education

PhD in Electrical Engineering or related field

Master’s degree in Electrical Engineering or related field

Bachelor’s degree in Electrical Engineering or related field

Tools

Python

JMP

Job description

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.

Role Summary

The Staff Engineer in System and Technology Product Group (STPG) owns defined technical scope across the full learning loop of NAND Test Chip Vehicle (TCV) development. This role drives pre-silicon validation, post-silicon characterization, simulation-to-silicon correlation, and technology learning to improve future NAND architectures. Success requires strong technical judgment, advanced data analysis capability, cross-functional collaboration, and the ability to independently drive complex technical issues to resolution while influencing design, process, technology development, and test stakeholders.

Main Responsibilities

• Own pre-silicon validation, simulation coverage, regression development, and correlation activities for TCV programs.
• Analyze simulation results to identify architecture, device, performance, and margin sensitivities that influence tape-out readiness.
• Own post-silicon validation, characterization, debug, and silicon learning activities for TCV devices.
• Drive root cause analysis of silicon anomalies and distinguish design, process, modeling, and test-related limitations.
• Define test modes, patterns, stress conditions, and characterization methodologies to maximize technology learning and data quality.
• Lead data-driven problem solving and influence cross-functional decisions through technical expertise and execution.

Other Responsibilities

• Collaborate with Design, Technology Development, Process Integration, and Test organizations to accelerate technology learning.
• Partner with Test Solutions Engineering to influence probe code, test flows, and characterization strategies.
• Develop technical documentation, best practices, and reusable methodologies that improve organizational learning.
• Mentor less-experienced engineers and promote knowledge sharing across teams.

AI Responsibilities

Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.

Minimum Qualifications / Experience

• PhD with ≥2 years, or Master’s degree with ≥5 years, or Bachelor’s degree with ≥7 years of relevant experience in Electrical Engineering, Materials Science, Chemical Engineering, Physics, or a related field, with demonstrated expertise in semiconductor industry.
• Demonstrated experience in both pre-silicon simulation/regression ownership and post-silicon validation for complex semiconductor designs.
• Experience driving technical problem resolution with a high degree of independence.

Must-Have Technical Skills

• Strong understanding of CMOS/MOSFET device physics, semiconductor devices, memory circuits, and NAND flash architectures.
• Experience with pre-silicon simulation environments, regression methodologies, and simulation-to-silicon correlation.
• Proficiency in data analysis, scripting, and statistical evaluation using Python, JMP, or equivalent tools.
• Working knowledge of DFT, probe test infrastructure, failure analysis, and silicon characterization methodologies.
• Experience applying advanced analytics, machine learning, or AI techniques to engineering datasets.

Must-Have Soft Skills

• Structured problem-solving and analytical decision-making.
• Cross-functional collaboration and stakeholder influence.
• Clear technical communication and technical documentation skills.
• Ability to independently manage ambiguity and drive execution to closure.

Highly Desirable / Preferred

• Deep experience with NAND flash architectures, array-periphery interactions, and test chip development.
• Experience with firmware-assisted test modes and experimental silicon features.
• Embodies Micron's Core Values: People - Respect, develop and empower others; Innovation - Drive continuous improvement and breakthrough thinking; Tenacity - Show grit and determination; Collaboration - Build trust and foster teamwork; Customer Focus - Deliver excellence and value; Speed - Act with purpose and set the pace.

About Micron Technology, Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience. To learn more, please visit micron.com/careers.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.