Sr Staff Product Engineer

Responsibilities

• Product Leadership & NPI Execution
• Lead end-to-end product lifecycle execution across multiple programs-from concept definition through characterization, qualification, customer release, and ramp to high-volume manufacturing (HVM).
• Define and drive product validation, characterization, and qualification strategies aligned with product requirements, reliability expectations, and customer use cases.
• Demonstrate a proven track record of successfully releasing multiple IC products into production and sustaining performance through volume ramp.
• Data Analysis, Characterization & Yield Strategy
• Apply advanced statistical analysis and data science techniques to characterize device electrical performance and parametric behavior.
• Develop robust methodologies for analyzing distributions, corner performance, and guard band optimization.
• Lead deep-dive investigations of yield excursions, parametric shifts, and failure mechanisms using structured statistical approaches and large-scale data analysis.
• Identify correlations across design, silicon, and test datasets to uncover root causes and improve product robustness.
• Establish scalable analytics frameworks, dashboards, and visualization tools to enable data-driven decision making across product lifecycle phases.
• Qualification, Reliability, ESD & Latch-Up Expertise
• Define and execute comprehensive product qualification strategies aligned to JEDEC and industry standards (e.g., JESD47, JESD22 series).
• Drive reliability stress planning and interpretation, including HTOL, HAST/uHAST, TC, ELFR, and associated qualification methodologies.
• Lead ESD and latch-up qualification strategy, data analysis, and failure resolution in alignment with product requirements.
• Analyze reliability data to assess failure mechanisms, lifetime projections, and margin to specification limits.
• Ensure qualification coverage, sample sizes, and stress conditions support defensible product release decisions.
• Partner with reliability and quality teams to resolve qualification risks and define mitigation strategies.
• Failure Analysis & Root Cause Investigation
• Lead complex failure analysis activities across electrical, parametric, ESD, latch-up, and reliability-related failures.
• Utilize data-driven approaches to correlate failure signatures with design, process, or test-related mechanisms.
• Drive cross-functional root cause investigations and ensure corrective actions are implemented and verified.
• Develop systematic approaches to failure classification, screening effectiveness, and defect pareto analysis.
• AI-Driven Engineering Efficiency
• Identify and drive opportunities to improve engineering efficiency through application of AI, machine learning, and advanced analytics in areas such as: Characterization data reduction and automation
• Anomaly detection and outlier classification
• Predictive yield and reliability modeling
• Develop or leverage intelligent workflows to accelerate insight generation and reduce manual analysis effort.
• Promote adoption of data-centric and AI-assisted methodologies to improve engineering productivity and decision quality.
• Technical Leadership & Cross-Functional Influence
• Serve as a recognized subject matter expert in product engineering, statistical analysis, reliability, and failure analysis.
• Lead cross-functional efforts across design, applications, reliability, and test teams to resolve highly complex technical challenges.
• Provide leadership in defining characterization plans, qualification strategies, and analysis methodologies.
• Mentor engineers in advanced statistical techniques, reliability interpretation, and structured problem solving.
• Strategic Problem Solving & Innovation
• Work on complex, ambiguous problems requiring evaluation of incomplete or conflicting data, applying conceptual and statistical thinking to determine optimal solutions.
• Anticipate technical risks in product performance, qualification adequacy, and reliability margins, and proactively drive improvements.
• Contribute to development of best practices in qualification methodology, data analysis, and engineering decision frameworks.
• Stakeholder Engagement & Organizational Impact
• Build and lead networks across global teams to align characterization strategy, qualification coverage, and product readiness.
• Communicate complex analytical findings, qualification results, and failure analysi

Additional Information

Applicants for this position must be currently authorized to work in the United States on a full-time basis. Renesas is unable to sponsor applicants for work visas for this position now or in the future. Hybrid - Morrisville, NC Renesas is a global leader in semiconductor solutions, enabling innovations across industrial, IoT, edge computing, and intelligent power applications. Our teams drive the development of next-generation products, including devices supporting Edge AI capabilities, by collaborating across design, product engineering, and manufacturing to deliver high-quality, scalable solutions worldwide.

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Company Intel

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