Staff Product Development Engineer

THE ROLE:

Returns Debug and RMA execution in Quality & Reliability organization, provide supportive functions to the organization to ensure customer quality issues are being addressed, evoking the required actions via failure analysis to improve product quality.

THE PERSON:

You will also need to possess strong verbal and written communication skills, which are essential when working with a global team. A proactive, outstanding teammate who focuses on teamwork, team building, and growing team success.

AMD's environment is fast-paced, results-oriented, and built upon a legion of forward-thinking people with a passion for winning technology!

KEY RESPONSIBILITIES:

• Perform System-level and board-level Failure Analysis (FA) for Data center CPU/GPU products, covering customer returns and field failures.
• Conduct System-Level Test (SLT) using internal test board or on customer platform to duplicate customer reported failures and isolate the cause of failure.
• Perform board power up test and functional test to isolate board or component level failure.
• Collaborate with ASIC Engineering teams for in-depth GPU ASIC/die-level investigations, fault isolation, and root cause analysis.
• Investigate Excursion and Critical Issues, supporting DPPM (VF/NFF) improvement initiatives.
• Drive test coverage analysis and enhancements to improve failure detection and mitigation.
• Partner with validation, firmware, and hardware teams to resolve hardware, software, and platform issues.
• Innovate, prototype, and evaluate new FA tools to improve GPU failure analysis capabilities.
• Knowledgeable in functional test and stress software to enhance debug efficiency.
• Provide technical assistance, resources, and equipment to support engineering teams in testing and debugging activities.
• Plan, set up, and install server racks with air and liquid cooling capabilities for advanced test infrastructure.
• Work closely with program managers and product line quality (PLQ)/customer Interacting teams to align failure analysis report writing with external customer communication.
• Document debug findings, root cause analysis, and corrective actions in clear, concise technical reports.
• Serve as the local product owner, responsible for tracking and releasing platform screening programs and BKC revision related to server rack level, board level and OSV programs.
• Act as the Go-To technical expert for owned products, supporting test program contents, FA methodologies, and customer queries.
• Proactively identify opportunities for process improvement, code quality enhancements, and hardware coverage expansion.
• Other duties as assigned by supervisor.

PREFERRED EXPERIENCE:

• Strong in either silicon or board level debug or Failure Analysis knowledge.
• Candidate should be analytical and detail-oriented, strongly interested in debugging complex systems, self-starter, and a fast learner
• Excellent skill in code development, familiarity with Linux and modern software tools/benchmarks and techniques for development.
• Understanding of GPU or x86 architecture knowledge is much preferred
• Knowledge or experience in server or data center hardware or platform is a plus.
• Experience working with power management features such as POST, P-states, etc.
• Knowledge of industry standards like PCIE, USB, or high bandwidth memory is a strong plus
• JTAG knowledge is a plus.
• Strong understanding of BIOS or memory firmware is a plus.
• Experience programming experience with C++, C#, Python, HTML, or JAVA.
• Experience with PC HW debugging, including voltage, networking, storage, and thermal control.
• Experience with building computer systems (desktops, laptops, servers, etc).
• Experience in server installation, configuration, and maintenance is a plus.
• Good analytical and problem-solving skills.
• Strong understanding of hardware debugging, test equipment (multimeters, oscilloscopes, thermal cameras, etc.), and system-level troubleshooting.
• Proficient in reading electronic schematics and electronic component datasheets.
• Proficient in AI tool or machine learning knowledge is a plus.

ACADEMIC CREDENTIALS:

• Bachelor's or master's degree in electrical and Electronic Engineering, Computer Engineering is preferred.