This engineer runs thermal, mechanical, and acoustic validation of GPU platform cooling solutions in a lab, operating server-based GPU test environments via headless Linux. Day to day they build Python test automation, analyze lab and manufacturing data, and collaborate with firmware, BIOS, and driver teams.
Execute thermal, mechanical, and acoustic validation for platform thermal solutions, including test method improvements and data collection.
Set up, configure, operate, and troubleshoot server-based GPU validation environments, using headless Linux, SSH, and remote-access tools to resolve system-level issues.
Partner with Thermal Mechanical Design, software diagnostics, BIOS, driver, and platform teams to validate GPU thermal features, fan-control approaches, and heatsink readiness.
Collaborate with firmware architects to validate, debug, and prototype GPU thermal-management and fan control features using Python-based tools and an understanding of low-level firmware.
Develop Python-based test automation and data-analysis tools.
Support the development of data analysis pipelines to collect, process, analyze, and visualize low-volume lab validation and high-volume manufacturing data.
Required Qualifications
Hands-on experience assembling, configuring, troubleshooting, or maintaining PCs and/or servers.
Strong familiarity with PC hardware and GPU terminology.
Familiarity with headless Linux command-line workflows, including SSH, tmux, and remote access.
Experience using Python for scripting, automation, data analysis, or engineering workflows.
Basic physics understanding of heat transfer, airflow pressure & flow rate, mechanical stress & strain, and acoustics.
Experience with data analysis required.
Experience with high-volume data engineering is a plus.
Preferred Qualifications
Experience in computer hardware, hardware validation, or computer engineering lab environment.
Experience with lab data acquisition equipment: data-acquisition systems (DAQs), oscilloscopes, thermal sensors, mechanical sensors, and acoustic measurement equipment.
Familiarity with C, C++, or other systems-programming languages is a plus.
Experience working with test automation, telemetry, manufacturing data, or hardware performance data.
Experience applying Agentic AI tools to test-data analysis or lab-workflow automation is a plus.