Senior Deep Learning Hardware Modeling Architect - LPU

Nvidia

Remote

Quick summary

Work type
Remote
Location
San Francisco, CA · Austin, TX · Boston, MA
Salary
$152,000–$241,500 / yr
Posted
2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $216k
This role $197k
$139k most similar roles pay here $276k

This role pays less than 66% of similar roles. Most pay $185,962–$246,150 — the shaded band above. At the midpoint, this role pays about $197k versus about $216k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 985 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 971 roles with salary data.

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At a glance

TL;DR · Senior Deep Learning Hardware Modeling Architect - LPU

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NVIDIA is seeking a Senior Deep Learning Hardware Modeling Architect to join its pioneering team focused on optimizing AI inference performance through hardware-software co-design. In this role, you will drive architectural specifications across multiple stakeholders, develop detailed component-level and system-level designs, and create executable models used by NVIDIA’s customers worldwide. Your responsibilities include ensuring high performance using robust C++ practices, algorithms, and parallelism, as well as resolving complex issues across chip and hardware subsystems in collaboration with various teams. Ideal candidates possess a strong background in C++, experience in RTL design, and an automation-centered mindset to enhance work efficiency. This role offers the chance to contribute significantly to cutting-edge LLM inference solutions at NVIDIA.

Skills

C++ RTL Chip Design Systems-Level Modeling Architectural Analysis Automation AI Efficiency提升工具 性能分析 数据结构优化 并行计算 软件架构设计 硬件-软件协同设计 LLM Inference Hardware

What you'll do

  • Drive architectural specifications to closure across multiple stakeholders.
  • Develop detailed written specifications for component and system designs.
  • Create executable models used by customers for AI inference solutions.
  • Ensure high performance through effective use of C++, algorithms, and parallelism.
  • Resolve complex performance and correctness issues across hardware subsystems.

What we're looking for

  • 5+ years of relevant experience in a technical field such as CS, EE, or Math.
  • Expert programming skills in C++ for developing high-performance software.
  • Experience in RTL design with understanding of chip design concepts.
  • Ability to develop and embody architectural specifications in executable models.
  • Strong automation mindset and desire to improve work efficiency using AI.

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