Senior Failure Analysis Engineer - Test Development

• Architect targeted test methods for hard-to-capture platform behaviors across GPU, server, and rack-scale environments.
• Invent new workload patterns, sequencing approaches, and stress combinations that reveal conditions not covered by conventional diagnostics.
• Build and maintain VPOD-based environments that support scalable experimentation, long-duration execution, and controlled reproduction studies.
• Use inference and training activity as system stimuli to probe platform limits, timing sensitivities, and failure-prone operating regions.
• Develop automation, scripting, and orchestration tools to launch workloads, monitor execution, collect logs, and analyze results at scale across Windows and Linux environments.
• Interpret telemetry, logs, and observed signatures to refine experiments, isolate trigger conditions, and improve confidence in reproduced behavior.
• Create AI-enabled execution flows that use internal FA knowledge and live inference to guide test branching, detect emerging patterns, and support faster triage decisions.
• Partner closely with FA, validation, diagnostics, firmware, and manufacturing teams to translate vague symptoms or sporadic field issues into targeted and repeatable test content.
• Document workload intent, test methods, reproduction conditions, and findings clearly so they can be reused across teams and incorporated into future FA workflows.
• Drive continuous improvement of test development methods, workload libraries, and failure reproduction strategies to expand FA coverage and reduce time to root cause.

• Proven track record of developing custom test methodologies for intermittent, low-occurrence, or otherwise difficult-to-observe failure modes.
• Strong foundation in GPU and server platform behavior, including system stress interactions, concurrency effects, and stability characterization.
• Demonstrated ability to build, run, and optimize VPOD environments and related infrastructure for large-scale FA or validation test execution.
• Hands-on familiarity with inference and training environments, including their use as controllable system stressors in platform investigation.
• Proficient in Python, shell scripting, and automation development for workload launch, orchestration, telemetry capture, and post-run analysis.
• Ability to interpret system data and debug artifacts to uncover meaningful signals and guide the next experimental step.
• Familiarity with diagnostics, firmware interactions, drivers, and hardware/software boundaries that influence failure behavior under stress workloads.
• Experience building AI-enabled test systems that incorporate internal engineering knowledge and support real-time inference during execution.
• Strong communication, documentation, collaboration, and presentation skills, with the ability to explain complex reproduction strategies and findings across technical teams.
• Experience with GPU data center infrastructure, AI/ML technologies, and non-standard workload development is a strong plus.

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.

• Secaucus, NJ

This role is not eligible for Visa sponsorship

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Benefits offered are described: AMD benefits at a glance .

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This posting is for an existing vacancy.