Senior Architect, Data Center Modeling
@ NVIDIA

Austin, TX
$300,000
On Site
Full Time
Posted 14 hours ago

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Job Details

About the Role

Imagine shaping the future of AI and computing at NVIDIA, one of the most innovative companies in the world. As a Senior Architect, Data Center Modeling, you will design and develop models for the next generation of GPU-accelerated datacenters.

What You'll Be Doing

  • Guide fundamental software design, architecture, and cost/power modeling.
  • Evangelize modern software architecture patterns and AI-driven tools.
  • Implement industry-leading software and dev-ops best practices.
  • Contribute hands-on to a business-critical, high-performance codebase.

What We Need To See

  • Bachelor's degree in a related field (MS preferred) and 8+ years’ experience.
  • Expertise in systems architecture and modeling including performance, power, and cost.
  • Exceptional Python programming skills along with strong mathematical abilities.
  • Proven experience contributing to scaled Python-based software projects.

Ways To Stand Out From The Crowd

  • Experience with accelerated server architecture design and hyperscale deployment.
  • Background in parallel computing, server architecture, or datacenter design.
  • Expertise in data analysis and visualization using pandas and similar tools.
  • A passion for evolving accelerated computing and AI technologies.

Key Skills/Competency

  • Architecture
  • Modeling
  • Design
  • Python
  • Performance
  • Cost
  • Power
  • Distributed Systems
  • AI
  • Datacenter
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How to Get Hired at NVIDIA

🎯 Tips for Getting Hired

  • Research NVIDIA's culture: Study their mission, projects, and team dynamics.
  • Customize your resume: Highlight architecture and Python expertise.
  • Emphasize your experience: Detail cost and power modeling work.
  • Interview preparation: Prepare examples of scalable design impacts.

📝 Interview Preparation Advice

Technical Preparation

Review GPU-accelerated computing concepts.
Practice performance and power modeling techniques.
Enhance Python and devops skills.
Study distributed system architecture best practices.

Behavioral Questions

Describe a project with scalable design.
Explain teamwork in cross-discipline projects.
Discuss problem-solving in high-pressure situations.
Share experience driving continuous improvement.

Frequently Asked Questions