HPC Performance Engineer

Nvidia

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
ORTXCAMA
Salary
$152,000–$241,500 / yr
Posted
53 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $206k
This role $197k
$141k most similar roles pay here $255k

This role pays less than 52% of similar roles. Most pay $176,200–$235,750 — the shaded band above. At the midpoint, this role pays about $197k versus about $206k 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 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · HPC Performance Engineer

As an HPC Performance Engineer within the NVHPC compilers and tools group, you will analyze High Performance Computing applications to improve performance through compiler optimizations and library enhancements. You will work with a diverse range of workloads, from small benchmarks on single-CPU cores to full-scale applications running on multi-node, multi-GPU systems. Your daily responsibilities include evaluating the impact of compilers, runtimes, device drivers, and system configurations on application performance while porting applications to various platforms and programming models. To succeed, you must possess expertise in Fortran, C, C++, OpenACC, OpenMP, MPI, CUDA, and Standard Language Parallelism. You will also utilize strong mathematical fundamentals in linear algebra and numerical methods to solve complex problems. This role focuses on the technical challenge of optimizing performance across CPU and GPU platforms within a dynamic development environment.

What you'll do

  • Analyze the impact of different compilers and optimizations on HPC application performance.
  • Evaluate how compiler and runtime components improve performance on CPU and GPU platforms.
  • Communicate compiler capability limits to application engineering teams to guide optimization paths.
  • Port HPC applications across various platforms and programming models.
  • Evaluate the impact of NVHPC package components, device drivers, and system configurations on performance.
  • Identify and implement optimizations for both small benchmarks and large multi-node, multi-GPU systems.

What we're looking for

  • BS/MS degree in Computer Science or a related engineering field is required.
  • Candidates must have at least 5 years of programming experience.
  • Proficiency in Fortran, C, and C++ is required, especially for parallel architectures.
  • Experience with OpenACC, OpenMP, MPI, CUDA, and Standard Language Parallelism is required.
  • Strong skills in performance analysis, tuning, and understanding of runtime environments are required.
  • Candidates must have strong mathematical fundamentals including linear algebra and numerical methods.
  • Experience with assembly language programming, debugging, and porting is a significant advantage.
  • A deep understanding of machine architectures and micro-architectures is preferred.

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