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Senior Deep Learning Performance Architect

NVIDIA· Architect
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Hybrid (US, CA, Remote), Hybrid (US, TX, Remote)$152k - $241.5kFull-timePosted 7mo ago

About the role

Senior DL Performance Architect to push AI Inference performance boundaries through hardware-software co-design, modeling LLM performance, and guiding AI system architecture and optimization.

Responsibilities

  • Design novel GPU and system architectures to advance AI Inference performance and efficiency
  • Construct, investigate, and test popular deep learning algorithms and applications
  • Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications
  • Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture
  • Collaborate across the company to guide the direction of AI, working with software, research, and product teams

Qualifications

  • MS or PhD in CS, EE, Math or equivalent experience, with 5+ years of relevant experience
  • Strong mathematical foundation in machine learning and deep learning
  • Expert programming skills in C, C++, and/or Python
  • Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack
  • Strong knowledge and coursework in computer architecture

Skills

Required:Mathematical foundation in ML/DLC/C++/PythonGPU computingHPC stackComputer architecture

Benefits

  • equity
  • benefits (see NVIDIA benefits page)
Last updated Aug 14, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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