Data Center Mechanical Engineer
Job Description
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We’re looking for a Data Center Mechanical Engineer to join our team during an exciting phase of growth. In this role, you’ll be responsible for leading the design, technical validation, and optimization of advanced thermal management systems, working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.
What You’ll Do
Lead the design review and technical validation of advanced thermal management systems for hyperscale data centers, with a specific focus on high-efficiency, liquid-first cooling topologies.
Design and model cooling infrastructure—including chillers, cooling towers, pumps, heat exchangers, and distribution piping—to handle the extreme heat loads from AI compute hardware.
Perform computational fluid dynamics (CFD) modeling to optimize airflow and liquid flow within the data center, ensuring thermal containment and efficiency.
Provide engineering guidance during the construction and commissioning process to ensure mechanical systems are installed and tuned for optimal performance (PUE/WUE).
Ensure all designs comply with ASHRAE, local building codes, and corporate sustainability standards.
Who You Are
Required Qualifications
B.S. in Mechanical Engineering.
6+ years of experience in the design, construction, and commissioning of large-scale HVAC or critical cooling systems.
Proven experience with water-side design, including fluid dynamics and pumping systems.
Preferred Qualifications
Professional Engineer (P.E.) license or equivalent chartership.
Direct experience with liquid-to-chip or rear-door heat exchanger (RDHX) cooling systems.
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TensorWave
View Company ProfileTensorWave is a premier, enterprise-grade cloud infrastructure provider engineered to orchestrate massive-scale artificial intelligence (AI) and high-performance computing (HPC) workloads. Operating as a high-velocity digital ecosystem, the company eliminates the operational friction and supply chain bottlenecks of legacy hyperscalers by exclusively deploying advanced AMD Instinct™ accelerators—including the MI300X and MI325X—across highly optimized bare-metal environments. Moving beyond the rigid memory constraints of traditional GPU cloud models, TensorWave provides industry-leading capacity with up to 288GB of HBM3e per accelerator, directly tackling the immense requirements of next-generation Large Language Models (LLMs) and complex machine learning training clusters. Under the hood, their UEC-ready networking architecture and direct liquid cooling systems seamlessly integrate into existing AI pipelines, ensuring ultra-low latency inference and blistering training speeds. What sets TensorWave apart is its uncompromising dedication to open-source democratization and performance accessibility; by bridging the gap between top-tier compute resources and massive cost-efficiency, the platform empowers scaling enterprises to radically accelerate AI innovation without the burden of building internal hardware infrastructure.
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