Senior Architect, Data Center Modeling

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +5 · Remote

This role focuses on designing and developing models for next-generation GPU-accelerated datacenters, specifically in cost and power modeling. It involves guiding software architecture, implementing best practices, and contributing to a critical codebase. The role requires strong Python programming, systems architecture, and modeling experience, with a preference for advanced degrees and experience in accelerated server architecture or parallel computing.

What you'd actually do

  1. Guiding the fundamental software design, architecture, and implementation of cost and power modeling of datacenter-scale accelerated computing platforms
  2. Evangelizing modern software architecture design patterns and tools, including AI-driven solutions, to accelerate development, enhance performance, and improve code quality across the team.
  3. Implementing industry-leading software and dev-ops best practices tailored for rapidly growing teams, fostering a culture of continuous improvement and innovation.
  4. Making hands-on and significant contributions to a business-critical codebase, directly impacting the future of high-performance computing and AI technologies.

Skills

Required

  • Bachelors degree in Computer Science, Computer Engineering, Electrical Engineering or related fields or equivalent experience
  • 8+ years of experience in systems architecture and modeling
  • performance, power, or cost modeling of distributed systems
  • Exceptional programming skills in Python
  • strong mathematical and analytical skills
  • Excellent interpersonal skills
  • Proven track record of contributions to scaled Python-based software projects

Nice to have

  • MS preferred
  • Experience with accelerated server architecture design and deployment, especially up to hyperscale
  • Background in parallel computing, server architecture, or datacenter design
  • Expertise in data analysis and visualization, especially pandas and associated technologies

What the JD emphasized

  • cost and power modeling
  • datacenter-scale accelerated computing platforms
  • AI-driven solutions
  • high-performance computing and AI technologies
  • systems architecture and modeling
  • performance, power, or cost modeling
  • Python-based software projects