Microsoft's cloud business continues to grow and the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance
Requirements
5+ years of work experience in managing product quality in the electronic industry
5+ years of direct engineering experience in hardware system issue resolution for GPU Servers
Versed in filtering through applicable debug data, like telemetry and logs to identify and investigate HW failure signatures
Experience with Liquid Cooling Systems in Data Centers
12+ years of experience in working with the modern server architectures – includes understanding of GPU, CPU methods for failure analysis, debugging or validation
8+ years of system level server debugging with an understanding of platform, power, system and network environments
3+ years of direct GPU related engineering experience in issue debug/test log review
Responsibilities
Develop and implement a robust supplier quality management strategy to ensure the data center hardware is manufactured at the highest level of quality standards
Lead quality issues and improvement task force to contain, mitigate, and resolve the top-quality issues at data centers
Conduct debug and failure analysis for GPU subsystems in the Azure fleet and drive resolution with partners and suppliers
Drive the continuous improvement process based on Root Cause Analysis (RCA) and identified opportunities
Responsible for quality readouts based on your telemetry data analysis, to bring clarity on status, actions across the organization and next steps for issue resolution
Establish Critical-to-Quality performance metrics to measure and improve product quality
Act as the voice of quality in the hardware change management process, ensuring quality requirements are considered and met and improved
Other
Master's Degree in Electrical Engineering, or related field AND 3+ years technical engineering experience
Ability to meet Microsoft, customer and/or government security screening requirements
Leadership skills and ability to collaborate with diverse teams and drive a call to action
Ability to analyze large data sets, extract key insights, and effectively present and communicate the results
Proficient communication and project management skills
