Staff/Principal Engineering Lead, TD RDA

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD.; Singapore; On-site; SGD 130,000 - 190,000; Full time

Job summary

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD. is seeking an experienced RDA leader to own the site-level strategy, analyze defects across NAND TD nodes, and drive continuous improvement through AI-enabled insights. You will collaborate with Process Integration, Yield, and Data Science to enhance device performance and yield.

The role requires mentoring engineers, defining metrics, and leading rapid containment actions while advancing inspection capabilities across global sites.

Qualifications

• Bachelor's degree with 7+ years relevant semiconductor experience, or Master's/PhD with 5+ years.
• Minimum 3+ years hands-on RDA experience in semiconductor manufacturing or equipment engineering.
• Demonstrated expertise in defect inspection, process monitoring, and yield learning.

Responsibilities

• Own the site-level RDA strategy and annual roadmap aligned to NAND TD technology nodes.
• Lead analysis of experimental and production flows to detect, classify, and trend defects.
• Establish, track, and report program health metrics (baseline health, detection rates, false positives, MTTR).
• Direct fast containment for defect excursions: trigger tool quarantines, define hold criteria, and lead 8D corrective actions.
• Architect inspection recipes and sampling strategies; optimize sensitivity, throughput, and cost of ownership.
• Partner with Process Integration, Yield, and Data Science to correlate inspection signals to device performance and yield.
• Influence supplier roadmaps; evaluate, qualify, and release next‑gen optical/e-beam inspection capabilities.
• Standardize and disseminate Best Known Methods (BKM) across global TD and manufacturing sites.
• Mentor, coach, and upskill engineers; develop succession plans and technical ladders within the RDA domain.
• Champion safety and continuous improvement (CIP); drive kaizen/lean initiatives that improve cycle time and learning velocity.
• Drive and enable an aggressive AI roadmap to enhance value of every engineer in the group

Skills

RDA experience

Defect inspection

Process monitoring

Yield learning

Statistical data analysis

Root cause analysis

DMAIC

Mentoring

Communication skills

Education

Bachelor's degree in semiconductors

Master's/PhD in related field

Tools

RDA systems

Optical/e-beam inspection tools

Job description

Required Responsibilities

• Own the site-level RDA strategy and annual roadmap aligned to NAND TD technology nodes.
• Lead analysis of experimental and production flows to detect, classify, and trend systematic and random defects.
• Establish, track, and report program health metrics (baseline health, detection rates, false positives, MTTR).
• Direct fast containment for defect excursions: trigger tool quarantines, define hold criteria, and lead 8D corrective actions.
• Architect inspection recipes and sampling strategies; optimize sensitivity, throughput, and cost of ownership.
• Partner with Process Integration, Yield, and Data Science to correlate inspection signals to device performance and yield.
• Influence supplier roadmaps; evaluate, qualify, and release next‑gen optical/e-beam inspection capabilities.
• Standardize and disseminate Best Known Methods (BKM) across global TD and manufacturing sites.
• Mentor, coach, and upskill engineers; develop succession plans and technical ladders within the RDA domain.
• Champion safety and continuous improvement (CIP); drive kaizen/lean initiatives that improve cycle time and learning velocity.
• Drive and enable an aggressive AI roadmap to enhance value of every engineer in the group

Key Responsibilities

• Serve as the technical lead for RDA methodologies and execution within NAND TD.
• Perform root cause analysis using statistical, image-based, and data-driven techniques.
• Develop, own, and communicate inspection and defect detection technology roadmaps.
• Define program health metrics and drive continuous improvement initiatives (CIP).
• Lead tool anomaly investigations, quarantine decisions, and corrective action planning.
• Embrace and enable innovations associated with AI to enable best in class insight generation while championing efficiency gains
• Collaborate globally to align Best Known Methods (BKM) across co-location sites pre/post transfer as well as across worldwide sites.

Stakeholder Collaboration

• Technology Development (TD) Process and Integration teams
• Yield Analysis and Data Science organizations
• Global Manufacturing and Operations
• Inspection/metrology equipment suppliers
• Program and engineering leadership across regions

Required Qualifications

• Bachelor's degree with 7+ years relevant semiconductor experience, or Master's/PhD with 5+ years.
• Minimum 3+ years hands-on RDA experience in semiconductor manufacturing or equipment engineering.
• Demonstrated expertise in defect inspection, process monitoring, and yield learning.

Technical Competencies

• Realtime Defect Analysis (RDA) systems and workflows.
• Optical and e-beam inspection technologies.
• Statistical data analysis, correlation development, and large dataset interpretation.
• Semiconductor process integration and technology development.
• Root cause analysis and systematic problem solving (e.g., 8D, DMAIC).

Leadership & Behavioural Competencies

• Recognized technical authority with the ability to influence with and without direct authority.
• Strong mentoring and coaching mindset with proven talent development outcomes.
• Clear, concise communication skills across technical and executive audiences.
• Ownership-driven, execution-focused; comfortable operating in ambiguity.

Impact & Success Measures

• Reduced defect-related yield loss and faster learning cycles.
• On-time qualification and adoption of next-generation inspection capabilities.
• Uplift in organizational RDA skill depth and succession pipeline.
• Alignment of inspection strategy and capability to future NAND nodes.

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.

AI Requirements

• Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes