Thermal​/Mechanical Engineer, NPI Technical Readiness

Meta is seeking a Staff Thermal Engineer to lead thermal architecture and new product introduction (NPI) efforts for large-scale data center infrastructure. In this role, you will define thermal strategies for next-generation server platforms, custom silicon, and high-density rack systems that power Meta's global infrastructure. You will drive thermal design from concept through mass production, partnering with silicon, mechanical, electrical, and manufacturing teams to ensure thermal performance, reliability, and manufacturability rmal/Mechanical Engineer, NPI Technical Readiness Responsibilities:

Conduct architecture reviews with hardware engineering teams to analyze and develop the most efficient interface and deployment strategy for mass production within the data center environment

Direct product reviews and deliver the technical readiness assessment for deployment alignment, with a specific focus on thermal, mechanical, spatial, and hardware compatibility

Perform airflow and liquid flow demand vs. capacity analysis, identifying the design margin and provide guidance on system control for efficient and reliable operation

Collaborate with cross-functional teams to define the requirements and deliver the necessary NUDD equipment to support the deployment

Partner with cross-functional teams and development partners to deliver harmonized new hardware platform roadmaps and secure an agreement on implementation milestones

Liaise with cross-functional partners in Meta’s Data Center Operations team to ascertain infrastructure deployment and operational requirements

Work with ODM/OEM vendors as necessary to define product specifications, development plans, and the integration strategy within the data center

Capture lessons learned from production issues and create corresponding test cases to address these issues in subsequent hardware platforms

Move to  or : 'Technical proficiency and experience in creating documentation suitable for users of all technical levels.'Domestic and/or international travel, up to 25%, is required

Minimum Qualifications:

Bachelor of Science degree in engineering, in thermal, mechanical, or equivalent technical experience is required

Minimum of 8 years of experience in development engineering, system validation testing or data center operation of AI/ML computer, networking equipment, and/or hyperscaler data center environments is mandatory

Possession of robust communication skills and a demonstrated capacity to influence cross-functional teams is essential

Domain knowledge in thermal engineering and/or mechanical engineering with hands-on experience with the designing, modeling, and validation of rack-level or data center cooling solutions

A proven history of navigating ambiguity and establishing processes for novel technologies, and successfully transitioning them into production, is required

Technical aptitude, evidenced by familiarity with ASIC, compute, storage, and network architecture and components, hardware troubleshooting and diagnosis capabilities, and/or hardware manufacturing processes

Experience operating within a global environment, including collaboration with remote teams, is required

Demonstrated experience with operational validation methodologies and verification activities pertinent to new product integration is expected

The ability to cultivate strong cross-functional relationships and influence policies and procedures to enhance the integration of hardware platforms into the data center

The capacity to mentor team members in evaluating and identifying superior methods for issue resolution and defining updates to tools and processes is expected

Preferred Qualifications:

Demonstrated experience with hardware development and/or data center design

Master’s or PhD in Electrical, Mechanical, Thermal Engineering Proven experience in developing for, or managing, large-scale server installations

Experience in utilizing AI-driven tools for workflow development

Expertise in AI/ML product integration and deployment in the data center at scale

Familiarity with the airflow or liquid flow CFDs such as 6

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