Title: Platform Debug and Triage Engineer - L3
Platform Debug and Triage Engineer
Job Title: Platform Debug and Triage Engineer
Job Location: Redmond, WA
Responsible for debugging and triaging issues on hardware platforms including hardware and software components, ensuring the smooth operation and performance of client computing systems. Perform silicon level debug to identify root causes with detailed reports and resolve all functional and triage failures. Functional validation of domains such as Power management, Graphics, Multimedia/Audio, Connectivity (BT, Wi-Fi, WWAN, GPS, NFC), security and manageability and others. Develop validation methodologies and test plans, execute validation plans, collaborate with other engineers for design optimization, trouble shooting and failure analysis. Collaborate with cross-functional teams to identify, analyse, and resolve platform-related issues. Develop and maintain debugging tools and scripts to automate the triage process.
Qualifications: Bachelor’s degree in computer science, Electrical Engineering, or a related field and above. Proven experience in debugging and triaging issues on hardware platforms. Experience in Windows Driver Frameworks, Windows kernel debugging along with system /user mode programming. Domain knowledge in relevant domains like PCIe, Memory, power management, FW, Boot loader (expert level in more than 1)
Understanding of GPU architecture with debug skills. Proficiency in programming languages such as Shell, C, C++, and Python. Architectural Knowledge (HW as well device driver) pertaining to a specific domain. Experience with debugging tools and techniques, including JTAG, WinDBG, LTB and kernel debugging. Hands-on on power consumption, debug bios, security and manageability logs and familiarity with relevant tools for debugging issues.
Preferred Qualifications: Knowledge of Nvidia architecture and platform technologies. Experience with memory dump analysis. Familiarity with virtualization technologies and cloud platforms. Experience with machine learning frameworks (Pytorch/Tensorflow) and their use in Data science. Knowledge in deploying and validating, AI, machine learning models.
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