Thermal Engineer (AI Infrastructure)

Location: Santa Clara, California, United States

Company

hirify.global develops high-power next-generation networking systems for AI infrastructures.

What you will do

• Design and develop thermal solutions including heatsinks, cold plates, liquid cooling loops, and other cooling systems.
• Lead thermal modeling and simulations using industry-standard tools to optimize system performance.
• Conduct thermal testing and validation against operational requirements.
• Collaborate with cross-functional teams to integrate thermal designs into broader system architectures.
• Build and manage technical relationships with suppliers to ensure high-quality thermal solutions.
• Troubleshoot thermal challenges and track emerging thermal engineering technologies, trends, and standards.

Requirements

• Bachelor’s degree in Mechanical Engineering or a related field with an emphasis on heat transfer is required; a master’s degree is preferred.
• 10+ years of experience in thermal design.
• 5+ years of experience designing thermal components and systems for data center network equipment is preferred.
• Proficiency with thermal modeling tools such as Flotherm, Flotherm-XT, and/or IcePak.
• Deep working knowledge of data center air-cooling technologies, including vapor chambers, heat pipes, phase-change devices, heat sinks, high-performance fans, thermal interface materials, environmental requirements, and rack-mounted ITE design constraints.
• Deep knowledge of heat transfer principles and their application in real-world scenarios.
• Strong problem-solving skills for complex thermal challenges.
• Excellent collaboration and communication skills for working with diverse teams and suppliers.
• A proactive mindset and interest in advancements in thermal technologies and AI infrastructure needs.

Nice to have

• Experience designing liquid-cooling components and loops.

Culture & Benefits

• Work on thermal solutions for next-generation AI and networking systems.
• Contribute directly to the performance and reliability of AI infrastructure.
• Collaborate with cross-functional teams and technical suppliers.