Senior Deep Learning Computer Architect

Nvidia

Actively hiring
Us, Ca, Santa Clara, US Posted 139 days ago $184,000–$287,500 / year
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At a glance

AI generated

TL;DR

As a Senior Deep Learning Computer Architect at NVIDIA, you will join our dynamic deep learning architecture team to design cutting-edge hardware accelerator and processor architectures for next-generation GPUs, enabling advanced AI applications across mobile, embedded, and datacenter platforms. Your daily responsibilities include analyzing the behavior of various deep learning methods, proposing innovative features to enhance performance, and collaborating with internal and external teams comprising DL researchers, hardware architects, and software engineers. To excel in this role, you should have a strong background in computer science or related fields, at least 5 years of experience in areas such as GPU architecture, performance analysis, LLM workloads optimization, and deep learning frameworks like PyTorch. Proficiency in C++ and Python is essential, along with expertise in GPU computing using CUDA. This role offers the opportunity to contribute significantly to a rapidly evolving field where real-time, cost-effective AI solutions are driving technological advancements.

Skills

C++ Python CUDA PyTorch GPU ComputerArchitecture DeepLearningKernels LLMWorkloads PerformanceAnalysis ParallelizationStrategies FusionStrategies

What you'll do

  • Design hardware accelerator and processor architectures for state-of-the-art machine learning.
  • Analyze behavior of various deep learning methods to propose new acceleration features.
  • Collaborate with DL researchers, hardware architects, and software engineers on projects.
  • Keep up-to-date with the latest deep learning research advancements continuously.
  • Study benefits of proposed architectural features for next-generation GPUs.

What we're looking for

  • MS or PhD in computer science, architecture, electrical engineering or related field.
  • 5+ years of experience in GPU architecture, system level design, and performance optimization.
  • Expertise in deep learning workloads, including parallelization and fusion strategies.
  • Proficiency with core deep learning kernels such as matrix multiply, attention, and convolution.
  • Fluency in C++ programming; familiarity with Python is a plus.
  • Experience with GPU computing using CUDA.
  • Knowledge of deep learning frameworks like PyTorch.

Market check

Salary context

This $184,000–$287,500 range sits above 74% of similar postings on FindRole.

Peer median band

$178,875–$262,400

Median floor and ceiling across peers.

Typical midpoint (25–75%)

$184,593–$240,675

Middle half of comparable postings.

Based on 240 comparable postings.

* 240 is the maximum number of comparable postings sampled.

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 802 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 798 roles with salary data.

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