Summary:

This role leads the thermal system and application architecture for Direct‑to‑Chip (D2C) liquid cooling solutions used in AI and ML data centers and serves as the technical authority responsible for defining, assessing, and integrating cooling components at the system level to ensure they meet the performance requirements of current and next‑generation AI and HPC processors. This individual will be a key technical interface for both prospective and existing customers, providing system‑level expertise in liquid‑cooled AI/ML applications.

Essential Functions:

System Architecture & Design

• Define and evaluate Direct-to-Chip liquid cooling architectures for AI/ML data centers
• Understand and assess the complete thermal path: Chip, Package, TIM, Cold Plate, Coolant, CDU, Heat Rejection
• Evaluate system-level trade-offs between thermal performance, cost, complexity, and scalability

Component & Integration Expertise

• Deep application-level understanding of: cold plates / cold plate assemblies, Thermal Interface Materials (TIMs), Coolant Distribution Units (CDUs), liquid loops and working fluids.  (contact mechanics, materials, channel concepts)
• Ability to evaluate and select components as part of an integrated system, not in isolation

Chip & Workload Understanding

• Strong understanding of the thermal characteristics of modern AI/ML chips, including: GPUs, AI accelerators, and high-end server CPUs, extremely high power densities and heat fluxes, hotspot behavior, transient loads, and package-level constraints
• Ability to translate chip packaging and roadmap trends (e.g., HBM, chiplets) into cooling architecture decisions

Data Center & Application Knowledge

• Proven background in AI/ML data centers and HPC environments
• Understanding of server and rack architectures, availability and redundancy requirements, integration of liquid cooling into existing data center infrastructure, operational, service, and reliability considerations

Customer & Market Interaction

• Act as the technical contact for customers in AI/ML data center applications
• Support customer discussions on cooling architecture selection, system-level trade-offs and constraints, integration of D2C liquid cooling into existing or planned infrastructures
• Translate customer requirements and use cases into technically sound system concepts
• Provide technical credibility in customer meetings, workshops, and technical reviews
• Support early-stage project evaluations, concept discussions, and feasibility assessments from a system architecture perspective

Qualifications:

• Bachelor's Degree in Mechanical Engineering, Physics, Material Sciences or related technical field. May consider relevant work experience in lieu of degree.  
• Demonstrated experience in AI/ML data centers or HPC environments
• Strong background in liquid cooling, ideally Direct-to-Chip
• Excellent system-level and architectural thinking
• Solid understanding of heat transfer and fluid flow principles at application level
• Ability to make and justify technical design and component selection decisions
• Excellent communication skills to clearly explain complex thermal system concepts to both technical and non-technical stakeholders, including customers
• Travel: Up to 25%