GPU Thermal Lab and Data Engineer

HCLTech; Markham; On-site; CAD 85,000 - 120,000; Full time

Job summary

HCLTech in Markham, Ontario is seeking a GPU Thermal Validation Engineer to join the hardware validation team. You will validate thermal, mechanical and acoustic performance of server platforms, improve test methods, and collect data to support design decisions.

You will set up and troubleshoot GPU validation environments on headless Linux, work with cross-functional teams, and develop Python automation and data-analysis tools to process lab and manufacturing data.

Qualifications

• Hands-on experience assembling, configuring, troubleshooting, or maintaining PCs and servers.
• Strong familiarity with PC hardware and GPU terminology.
• Experience with headless Linux workflows (SSH, tmux) and command-line tools.
• Proficiency in Python for scripting, automation and data analysis.
• Solid data analysis experience and ability to work with validation data.
• Experience with high-volume data engineering is a plus.

Responsibilities

• 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.

Skills

PC/server hardware

GPU terminology

Python scripting

Data analysis

High-volume data engineering (plus)

Tools

Linux (headless, SSH, tmux)

Python (automation)

Data analysis tools

Job description

Key Responsibilities

• 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.