Staff Yield Engineer

Renesas Electronics•San Jose, CA

About The Position

Renesas is seeking a Staff Foundry Yield Engineer to drive yield improvement, support new product introduction and manufacturing transfers, analyze yield and defect data, and provide technical support for foundry manufacturing issues. The role works closely with external foundry partners and internal cross-functional teams to support manufacturing performance, product ramp, excursion resolution, and continuous improvement in yield, quality, cost, and engineering efficiency. The engineer analyzes manufacturing, defect, inline, electrical test, wafer-sort, and wafer-level data to identify yield-loss mechanisms and opportunities. The position also supports qualification, safe launch, manufacturing readiness, production ramp, and risk assessment; coordinates root-cause analysis and corrective actions for yield excursions; and develops reusable analysis methods, dashboards, and reports. The role serves as a technical interface between foundries and internal engineering organizations, communicates findings and recommendations, and maintains engineering documentation and best practices.

Requirements

Bachelor's or Master's degree in Electrical Engineering, Microelectronics, Semiconductor Engineering, Materials Science, Physics, or a related technical field.
Solid understanding of semiconductor manufacturing processes, device fundamentals, and manufacturing or yield engineering.
Relevant experience in semiconductor yield engineering, process engineering, process integration, product engineering, or foundry engineering.
Strong experience with manufacturing and yield data analysis, including inline, electrical test, wafer sort, defect, and wafer-level data.
Strong statistical problem-solving and root-cause-analysis skills.
Experience with statistical or data-analysis tools such as JMP, Spotfire, Exensio/PDF, or equivalent.
Ability to work effectively with external manufacturing partners and cross-functional engineering teams.
Strong written and verbal communication skills.

Nice To Haves

Experience working with semiconductor foundries or outsourced wafer manufacturing.
Experience with NPI, manufacturing transfer, qualification, safe launch, and production ramp.
Knowledge of SPC, Cp/Cpk, D0/defect-density analysis, wafer-map analysis, correlation analysis, and statistical data mining.
Experience resolving complex manufacturing yield excursions and driving corrective actions.
Experience developing automated data-analysis or reporting workflows.
Exposure to AI/ML-assisted semiconductor data analytics.

Responsibilities

Monitor and analyze manufacturing yield, defect, inline, electrical test, wafer-sort, and related production data.
Identify yield-loss mechanisms and improvement opportunities through statistical analysis, wafer-level analysis, correlation, and data mining.
Partner with foundries and internal engineering teams to develop and implement yield-improvement actions.
Benchmark foundry performance and identify opportunities to improve yield entitlement and manufacturing cost.
Support new product introduction, manufacturing transfer, qualification, safe launch, and production ramp activities.
Develop data-analysis and monitoring plans to assess manufacturing readiness and identify potential risks.
Track yield and manufacturing performance during product introduction and ramp, and drive issues to closure.
Support qualification and transfer schedules through collaboration with foundry and internal stakeholders.
Analyze low-yield events, manufacturing excursions, abnormal defect patterns, and other quality-related issues in a timely manner.
Correlate manufacturing, electrical, and test data to support root-cause identification.
Work with foundry, Product Engineering, Quality, Test Engineering, and other technical teams on containment, corrective actions, and continuous improvement.
Provide data-driven technical recommendations for manufacturing disposition and risk assessment.
Apply statistical and visualization tools for yield analysis and data mining.
Develop and improve reusable analysis methods, dashboards, and reports to increase engineering efficiency.
Support evaluation, user acceptance testing, and deployment of new yield-analysis capabilities and engineering tools.
Explore automation and AI/ML-assisted approaches to improve yield analytics and engineering productivity.
Serve as a technical interface between external foundries and internal engineering organizations.
Lead or participate in technical interlock meetings covering yield, manufacturing capacity, excursions, NPI, and manufacturing transfers.
Communicate technical findings, risks, recommendations, and improvement plans to engineering teams and management.
Develop and maintain engineering documentation, analysis methodologies, and best practices.