Interface with multiple cross functional team members to Reproduce, Isolate and Root cause Failures. ACADEMIC CREDENTIALS: Bachelor's or master's degree in electrical engineering, Computer Engineering, or related field.
Numbers & Facts
Location
Austin, TX
Description
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