New 
Manufacturing Test Lead
 Microsoft | |
 United States, California, Mountain View | |
 Jul 13, 2025 | |
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OverviewMicrosoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft's expanding Cloud Infrastructure and responsible for powering Microsoft's "Intelligent Cloud" mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and deliver trusted experience to customers and partners worldwide and we are looking for passionate, high-energy engineers to help achieve that mission. As Microsoft's cloud business continues to grow, the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal, the Hardware, Infrastructure Management, and Fundamentals Engineering (HIFE) team is instrumental in defining and delivering operational measures of success for hardware manufacturing, improving the planning process, quality, delivery, scale, and sustainability related to Microsoft cloud hardware. We are looking for seasoned engineers with a dedicated passion for customer focused solutions, insight, and industry knowledge to envision and implement future technical solutions that will manage and optimize the Cloud infrastructure. We are looking for a Manufacturing Test Lead to join our team. Join us in this exciting AI revolution. Be part of the infrastructure engineering taskforce to fuel this world changing mission.
ResponsibilitiesDefine and lead end-to-end manufacturing test strategies for PCBAs, storage enclosures, and rack-level systems.Leads the development of test hardware, software, and firmware to validate the functionality of complex systems including GPUs, CPUs, and liquid-cooled platforms, ensuring alignment with product design and performance goals.Develop test plans and validation metrics for GPU-based platforms (e.g., NVIDIA HGX, GB200), covering bring-up, functional, performance, and stress diagnostics.Integrate AI/ML models to dynamically adjust test coverage based on historical data, product complexity, and risk profiles.Implement AI-driven anomaly detection systems to flag test escapes and reduce false positives in real time.Designs and delivers end-to-end test solutions, particularly for advanced liquid cooling technologies, addressing both macro and micro-level thermal transfer challenges (e.g., fluids, pumps, manifolds, connectors).Collaborates across multidisciplinary teams-mechanical, electrical, process, and production engineering-to integrate test strategies early in the product lifecycle and ensure seamless execution during manufacturing.Defines and maintains test architecture and core test content, including reusable scripts and test cases, for both blade-level and rack-level systems, ensuring scalability and consistency across product lines.Monitors production yield and test data, identifies systemic issues, and drives root cause analysis and corrective actions to improve test coverage, product quality, and manufacturing efficiency.Assesses manufacturing test readinessbefore each NPI (New Product Introduction) build, conducting risk assessments and coordinating mitigation plans with internal and external stakeholders.Initiates early engagement in design phasesto identify test coverage gaps, develop new test materials, and establish successful metrics to ensure quality and reliability from prototype to production.Ensures comprehensive documentation and verification coverageacross all product stages, mapping test cases to customer impact and business value, including coverage ROI and cost rationalization.Drive continuous improvement initiativesby analyzing test system data, eliminating non-value-added processes, and enhancing test effectiveness and efficiency.Engages with CM/ODM partners to understand production capabilities and limitations, ensuring supply chain alignment and consistent delivery of high-quality products.Leverage predictive analytics and machine learning to forecast failure trends and proactively mitigate risks.Evaluate AI readiness of supplier test systems and drive adoption of intelligent test solutions across the ecosystem.Collaborate with data science teams to develop AI tools that support test optimization and decision-making. | |