Failure Analysis & Validation Engineer

TITLE: Failure Analysis & Validation Engineer

LOCATION: Austin, TX (ONSITE)

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 Fails.

• 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 to engineering workflows is preferred.

ACADEMIC CREDENTIALS:

Bachelor's or master's degree in electrical engineering, Computer Engineering, or related field