Principal Thermal Engineer - AI System

Core Responsibilities

• Hands-on system thermal design.
• Own system-level thermal design from early concept through production, optimizing airflow, heatsinks, cold plates, heat exchangers, and liquid cooling hardware for very high-power GPUs, CPUs, VRs, and memory.
• Liquid and air cooling implementation. Design direct-to-chip liquid cooling solutions (cold plates, manifolds, tubing, quick-disconnects), support hybrid platforms, and own airflow design including fan selection, ducting, zoning, and impedance reduction.
• Modeling, lab validation, and correlation. Perform thermal and CFD modeling to guide placement and layout, instrument systems for validation, execute characterization and margin testing under real AI workloads, and correlate simulation with lab data.
• Bring-up, debug, and issue resolution. Lead thermal bring-up across EVT/DVT/PVT, debug hotspots, instability, and flow anomalies, and drive root-cause analysis with permanent fixes through factory ramp and field deployment.
• Cross-functional leadership. Work closely with mechanical, hardware, power, firmware, SI, and manufacturing teams to ensure thermal considerations are embedded into board layouts, mechanical stackups, and rack packaging; set thermal methodology and mentor engineers.

Required Qualifications & Skills

• Education: Bachelor's or Master's in Mechanical Engineering, Thermal Engineering, or a related discipline.
• Experience: 10+ years of hands-on thermal design for servers, GPU platforms, HPC systems, or high-power electronics, with proven delivery of air-cooled and/or liquid-cooled systems into production and direct involvement in bring-up, validation, and manufacturing ramp. Hyperscale deployment experience strongly preferred.
• Technical expertise: Strong hands-on knowledge of airflow and thermal design for high-power servers, direct-to-chip liquid cooling systems, cold plates/pumps/manifolds/heat exchangers, and CFD/thermal modeling tools; deep understanding of thermal-power-reliability relationships in AI/GPU systems.
• Working style: Strong individual contributor able to own problems end-to-end, comfortable debugging physical systems in the lab, and a clear communicator who translates thermal data into actionable design changes.