Senior Systems Software Engineer - GPU Performance at Scale

Nvidia

Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA
Salary
$184,000–$287,500 / yr
Posted
11 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $210k
This role $236k
$153k most similar roles pay here $302k

This role pays more than 82% of similar roles. Most pay $184,112–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $210k 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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View all roles at Nvidia

At a glance

TL;DR · Senior Systems Software Engineer - GPU Performance at Scale

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As a Senior Systems Software Engineer at NVIDIA, you will join a dynamic team driving innovation in AI and GPU computing by contributing to the development of high-performance computing hardware and software. Your primary responsibilities include leading the implementation of performance practices for large-scale GPU infrastructure, aligning next-generation AI workloads with datacenter builds, and developing engineering solutions that provide continuous insights into AI workload performance. You will collaborate closely with researchers, developers, and customers to craft improved workflows and develop new solutions, engaging with HPC, OS, CPU, GPU compute, and systems specialists to optimize large-scale performance platforms. Essential skills include a deep understanding of accelerated computing software stacks like CUDA, experience with cloud and container-based architectures such as Slurm and Docker, strong programming in C/C++/Python/Bash, and expertise in Linux systems programming and optimization.

Skills

CUDA Slurm Python C C++ Bash Docker Linux HPC Container Technology Virtualization Cloud Platform Solutions Systems Architecture Performance Optimization Linux Systems Programming

What you'll do

  • Lead implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools and methodologies.
  • Align next-generation AI workloads with NVIDIA’s datacenter builds for GPUs, CPUs, and networking hardware early on.
  • Develop continuous insights into evolving AI workload performance, identifying improvements and regressions swiftly.
  • Decompose complex performance or stability issues to identify root causes efficiently.
  • Collaborate with SW and FW teams to develop methods and tools for resolving critical firmware and software issues.

What we're looking for

  • Proven understanding of accelerated computing software stacks (CUDA).
  • Strong programming skills in C/C++/Python/Bash and experience with modern cloud architectures like Slurm.
  • Deep expertise in systems architecture, focusing on performance optimization.
  • Experience supporting high-performance computing or deep learning workloads.
  • BS in Engineering, Mathematics, Physics, Computer Science or equivalent; MS/PhD preferred with 8+ years of relevant experience.

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