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System Software Architect, AI Hardware and Software Performance

Salary not listed • China, Shanghai • Full-time

Posted 12d ago

Job Location

China, Shanghai

Tech Stack

Remote Work Policy

On-site

Employment Type

Full-time

Categories

AI Infrastructure Engineer

About the job

NVIDIA's Performance Lab (PerfLab) is seeking a System Software Architect to define the technical direction for platforms that evaluate the performance and quality of accelerated computing workloads. This role involves building platform components, leading projects from discovery to deployment, and collaborating with global NVIDIA teams to improve how AI performance is measured and understood. The architect will shape the future of large language models, agentic AI, and emerging HPC and AI workloads.

Responsibilities

  • Define the technical direction and architecture for major areas of benchmark infrastructure.
  • Lead the implementation of reusable software, services, and workflows for benchmark automation.
  • Establish engineering approaches to improve reliability, scalability, observability, maintainability, and reproducibility of benchmark campaigns.
  • Stay hands-on with AI benchmarking, analysis, and benchmark design to inform platform investments.
  • Lead delivery across team boundaries, aligning partner teams and managing risks.
  • Raise the engineering bar through reviews, standards, and mentoring.
  • Contribute to the strategy and development of internal and open-source projects.

Requirements

  • M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering (or equivalent experience).
  • 10+ years of hands-on experience in developing system software, distributed systems, or AI systems.
  • Strong Python and software engineering expertise, with a track record of building and operating production-quality tools, services, or automation frameworks.
  • Proven technical leadership on sophisticated, multi-functional projects.
  • Experience in quantitative analysis of AI hardware and systems, including performance, architecture evaluation, and power efficiency.
  • Experience in operating distributed or cloud-native systems at scale.
  • Excellent communication, influence, presentation, and cross-functional coordination skills.
  • A record of mentoring engineers and raising engineering quality.