Product Development Engineer
Hybrid (Austin, TX)$154.8kFull-timePosted 5d ago
About the role
Role focused on improving quality and reliability of AMD’s Server CPUs and Instinct accelerators by turning manufacturing and test data into actionable analytics and ML solutions; involves cross-functional collaboration and deploying production-grade analytics to optimize yield, quality, and cost.
Responsibilities
- Partner with Product Engineering, Test Engineering, Yield Engineering, Quality, and Operations to identify, define, and prioritize analytics and machine‑learning use cases that materially improve yield, quality, and cost.
- Develop and deploy ML/AI solutions for parametric outlier screening, drift detection, and excursion/anomaly detection across wafer, lot, site, and package dimensions.
- Perform in‑depth root‑cause analysis of yield loss and DPPM drivers by correlating test, fab, assembly, and design variables; distinguish systemic issues from statistical noise.
- Build, productionize, and maintain yield and quality analytics within AMD’s AVA analytics platform, moving models from experimentation to scalable deployment.
- Drive adaptive test, screening, and binning strategies using data‑driven insights to optimize product quality and manufacturing efficiency.
- Author clear technical documentation and reports; present findings and recommendations to cross‑functional teams and executive audiences.
- Contribute reusable code, analytics frameworks, and best practices that elevate team capability and accelerate future development.
Qualifications
- Strong background in semiconductor product development, yield engineering, or test engineering, with hands‑on experience analyzing high‑volume manufacturing data.
- Solid foundations in statistics and machine learning, including hypothesis testing, DOE/RSM, regression, classification, outlier detection, time‑series analysis, and anomaly detection.
- Familiarity with Python and SQL for data analysis and modeling (e.g., pandas, NumPy, scikit‑learn), general coding experience and demonstrated past ability in related scientific computing work.
- Practical knowledge of semiconductor manufacturing and test flows, including wafer sort and final test, binning strategies, DPPM analysis, reliability screens, and excursion management.
- Familiarity with yield analytics ecosystems similar to AMD’s environment; experience with server‑class CPUs and/or accelerator/GPU products is highly desirable.
- Demonstrated ability to deploy analytics or ML solutions into production environments, not just develop them in notebooks.
Skills
Required:Analytical problem solvingCross-functional collaborationPythonSQLStatistics
Last updated Oct 22, 2026. Interested? Apply on the company site.
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