Failure Analysis and Validation Engineer

Pay Range: $56.48hr - $59.62hr

KEY RESPONSIBILITIES:

• Develop and execute DOEs to validate silicon-, board-, and system-level failures.
• Bring up server platforms and test stations to support failure analysis for NPI and production.
• Debug hardware, firmware, driver, power, thermal, PCIe, and memory failures.
• Analyze logs, telemetry, and test data to identify failure signatures and dependencies.
• Develop and validate diagnostics, stress tests, and functional tests.
• Interface with multiple cross-functional team members to reproduce, isolate, and root-cause failures.
• Develop automation for FA workflows.
• Configure and maintain Windows- and Linux-based server test environments.
• Document processes, technical findings, and deliver clear FA reports and reviews.
• Optimize lab workflows and test capability to reduce turnaround time and system downtime.
• Analyze large datasets, develop dashboards, and generate technical reports.
• Travel to contract manufacturing sites to assist with bring-up and training.

PREFERRED EXPERIENCE:

• Strong EE fundamentals, knowledgeable in GPU/CPU architecture, post-silicon validation, platform debug, or test development.
• 5+ years of experience in test, debug, or validation of semiconductor assemblies.
• Strong knowledge of PCIe, memory, power management, and thermal-control subsystems.
• Experience debugging firmware, drivers, operating systems, and hardware interactions.
• Experience with firmware tuning, PVT characterization, voltage, temperature, and frequency margining.
• Programming and automation experience in Python, shell scripting, C++, C#, or equivalent languages.
• Proficiency with oscilloscopes, logic analyzers, multimeters, regulated power supplies, and thermal cameras.
• Ability to interpret schematics, component datasheets, logs, telemetry, and validation data.
• Experience with GPU data-center platforms and air- or liquid-cooled infrastructure is preferred.
• Experience working with AI tools or agent-based automation in engineering workflows is preferred.

ACADEMIC CREDENTIALS:

Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, or a related field.