Sr. Product Development Engineer

Advanced Micro Devices, Inc•Austin, TX

About The Position

AMD is hiring a Sr. Product Development Engineer to research, design, develop, and support software-driven system-level test (SLT) solutions for datacenter server processors throughout the product development life cycle. The role develops, debugs, and enhances test software, automation frameworks, data-analysis pipelines, and characterization flows used in semiconductor validation and manufacturing. It addresses complex engineering problems involving large-scale data sets and system behavior, in coordination with cross-functional teams. The engineer develops and improves SLT software, test programs, and characterization flows from post-silicon bring-up through volume production. The role applies statistical analysis and machine-learning techniques to characterization and manufacturing data to support silicon debug, yield optimization, screening effectiveness, and product quality. It also builds and maintains automation and analytics tools, analyzes test yield and performance, and provides reports, dashboards, and visualizations to guide engineering and manufacturing decisions. Under supervision, the engineer exercises judgment within established company procedures to select appropriate software methodologies, statistical techniques, machine-learning approaches, and evaluation criteria. The position requires a master’s degree or foreign equivalent in a specified computing-related field or a related field. Required experience may be gained through graduate-level coursework, research, or internship experience; no amount of prior experience is specified. Travel is not required.

Requirements

Master’s degree or foreign equivalent in Computer Science, Systems Software Engineering, Software Engineering, Computing and Information Science, or a related field.
Knowledge of computer-science fundamentals, including algorithms, data structures, and object-oriented software design.
Experience developing and debugging software systems for system-level testing, automation, and data analytics.
Knowledge of statistical analysis, machine-learning techniques, and data modeling for improving performance, yield, and quality metrics.
Experience working with large-scale engineering data sets and automated data-processing pipelines.
Experience with complex systems integrating software, data analytics, and hardware-validation environments.
Programming and scripting experience with Python, SQL, Java, and Bash.
Experience with data analytics and visualization tools: Power BI, Dataiku, and Snowflake.
Experience with software development environments: Linux, Git, and Jupyter Notebook.
Experience with Python libraries for data processing, statistical analysis, visualization, and applied machine learning.
Required experience may be gained through graduate-level coursework, research, or internship experience; no specific amount of experience is required.

Responsibilities

Research, design, develop, support, and improve software-driven system-level test (SLT) solutions, software, test programs, and characterization flows for datacenter server processors throughout the product life cycle.
Develop and extend software-based characterization and screening workflows using existing SLT test content, automated test algorithms, and configurable test frameworks.
Analyze post-silicon characterization and manufacturing data using statistical techniques, including Pareto, trend, and correlation analysis, to support silicon debug, yield optimization, and quality improvements.
Apply machine-learning and data-driven modeling techniques to identify failure signatures, improve screening effectiveness and test performance metrics, and enhance product quality.
Design, implement, and maintain SLT test-flow software, including version control, configuration management, revision control, and optimization of test conditions for screening efficiency and throughput.
Develop, bring up, and debug test programs, test patterns, and test algorithms across wafer-sort and final-test environments.
Debug and resolve issues involving test software, automation scripts, analytics pipelines, diagnostic tools, test-hardware interfaces, methods, and device-specific intellectual property.
Collaborate with ATE, validation, design, manufacturing, and fabrication teams to analyze system-level behavior, identify yield or quality root causes, and implement software-driven test and process improvements.
Perform SLT yield and performance analysis and generate statistical reports, dashboards, and visualizations with data-driven recommendations.
Develop automation and analytics tools using Python, SQL, scripting languages, and data-analysis libraries to process large SLT data sets and enable continuous integration of test results and quality metrics.
Apply algorithms, data structures, and object-oriented design to improve the reliability, scalability, and maintainability of SLT software systems.
Select appropriate software methodologies, statistical techniques, machine-learning approaches, and evaluation criteria within defined company procedures and practices.