Application Engineer

Summary: This role leads the thermal system and application architecture for Directu2011tou2011Chip (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 nextu2011generation AI and HPC processors. This individual will be a key technical interface for both prospective and existing customers, providing systemu2011level expertise in liquidu2011cooled AI/ML applications. Essential Functions: System Architecture & Design u2022 Define and evaluate Direct-to-Chip liquid cooling architectures for AI/ML data centers u2022 Understand and assess the complete thermal path: Chip, Package, TIM, Cold Plate, Coolant, CDU, Heat Rejection u2022 Evaluate system-level trade-offs between thermal performance, cost, complexity, and scalability Component & Integration Expertise u2022 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) u2022 Ability to evaluate and select components as part of an integrated system, not in isolation Chip & Workload Understanding u2022 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 u2022 Ability to translate chip packaging and roadmap trends (e.g., HBM, chiplets) into cooling architecture decisions Data Center & Application Knowledge u2022 Proven background in AI/ML data centers and HPC environments u2022 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 u2022 Act as the technical contact for customers in AI/ML data center applications u2022 Support customer discussions on cooling architecture selection, system-level trade-offs and constraints, integration of D2C liquid cooling into existing or planned infrastructures u2022 Translate customer requirements and use cases into technically sound system concepts u2022 Provide technical credibility in customer meetings, workshops, and technical reviews u2022 Support early-stage project evaluations, concept discussions, and feasibility assessments from a system architecture perspective Qualifications: u2022 Bachelor's Degree in Mechanical Engineering, Physics, Material Sciences or related technical field. May consider relevant work experience in lieu of degree. u2022 Demonstrated experience in AI/ML data centers or HPC environments u2022 Strong background in liquid cooling, ideally Direct-to-Chip u2022 Excellent system-level and architectural thinking u2022 Solid understanding of heat transfer and fluid flow principles at application level u2022 Ability to make and justify technical design and component selection decisions u2022 Excellent communication skills to clearly explain complex thermal system concepts to both technical and non-technical stakeholders, including customers u2022 Travel: Up to 25% Full-TimeRogers Corporation (u201cRogersu201d) maintains a continuing policy of non-discrimination in employment. It is Rogers policy to provide equal opportunity and access for all persons, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or status as a disabled veteran or other protected veteran, in all phases of the employment process and in compliance with applicable federal, state, and local laws and regulations.

Created: 2026-03-07