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TensorWaveTE

Data Center Design Engineer – 3D Modeling Specialist

TensorWave is a pioneering AI-focused cloud platform that leverages AMD's MI300X accelerators, enabling organizations to optimize AI workloads with enhanced performance and lower costs.

TensorWave

Employee count: 11-50

United States only

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TensorWave is seeking a Data Center Design Engineer with expertise in 3D modeling to support the planning and visualization of complex data center infrastructure.

Requirements

  • Develop and maintain high-fidelity 3D models of data center infrastructure
  • Translate 2D designs, engineering drawings, and specifications into coordinated 3D models
  • Perform clash detection, spatial analysis, and design validation
  • Collaborate with multidisciplinary teams to transform conceptual designs into precise 3D representations
  • Contribute to the development of data center design standards and modeling templates

Benefits

  • Stock Options
  • 100% paid Medical, Dental, and Vision insurance
  • Life and Voluntary Supplemental Insurance
  • Short Term Disability Insurance
  • Flexible Spending Account
  • 401(k)
  • Flexible PTO
  • Paid Holidays
  • Parental Leave
  • Mental Health Benefits through Spring Health

About the job

Apply before

Posted on

Job type

Full Time

Experience level

Mid-level

Location requirements

Hiring timezones

United States +/- 0 hours

About TensorWave

Learn more about TensorWave and their company culture.

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TensorWave is a cutting-edge cloud platform designed specifically for AI workloads, leveraging AMD's MI300X accelerators and a best-in-class inference engine. The platform offers innovative solutions for training, fine-tuning, and inference, providing users with faster, scalable, and user-friendly options compared to the competition. As the first launch partner utilizing AMD's MI300X GPUs, TensorWave is positioned to redefine AI compute capabilities, delivering immediate availability and performance enhancements.

TensorWave enables enterprises to harness the full power of artificial intelligence without the complexities often associated with model training and inference. It features both bare-metal nodes and fully-managed Kubernetes clusters, allowing users to choose the configuration that best suits their operational needs. The platform seamlessly integrates with popular machine learning frameworks like PyTorch and TensorFlow, requiring no code modifications from users. Security and cost-effectiveness are also prioritized, ensuring that sensitive data remains protected while providing a lower total cost of ownership without compromising on quality.

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TensorWave

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