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トレンド企業

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求人NVIDIA

Senior HPC Performance Engineer

NVIDIA

Senior HPC Performance Engineer

NVIDIA

US

·

On-site

·

Full-time

·

2d ago

As a member of our team in NVIDIA's NVHPC compilers & tools group, you will analyze and run High Performance Computing (HPC) applications on HPC servers and systems to gain insight into the performance characteristics of these applications. The applications you'll work with range from small synthetic benchmarks that use a single core to full applications that utilize all of the resources on distributed-memory systems with heterogeneous compute nodes including CPUs, GPUs and many-core processors. In this role you will analyze these applications and identify optimization opportunities for compiler development teams and application engineering teams.

What you’ll be doing:

  • Assist customers GPU accelerate HPC applications.

  • Analyze High Performance Computing (HPC) applications to better understand their performance characteristics.

  • Provide advise and drive compiler and applications engineering development teams based on the analysis of these HPC applications.

What we need to see:

  • BS/MS or equivalent experience in Computer Science or related engineering field.

  • 8+ Years of programming experience.

  • Solid understanding of Fortran/C/C++, as well as programming techniques, especially for parallel architectures; preferably for compilers

  • Experience with OpenACC, OpenMP, MPI, and CUDA.

  • Strong skills in performance analysis and tuning, as well as a broad understanding of parallel applications development tools and runtime environments.

  • Strong mathematical fundamentals, including linear algebra and numerical methods.

  • Understand performance considerations, tradeoffs and impact.

  • Expert interpersonal skills, logical approach to problem solving, good time management and task prioritization skills. Excellent written and verbal communication skills, along with the ability to work in a dynamic product oriented team.

Ways to stand out from the crowd:

  • You have a deep understanding of machine architectures and micro-architectures.

  • Experience with debugging and porting as well as assembly language programming is a significant advantage.

  • Experience is leading and/or managing projects is a plus.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 21, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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応募クリック数

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模擬応募者数

0

スクラップ

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NVIDIAについて

NVIDIA

NVIDIA

Public

A computing platform company operating at the intersection of graphics, HPC, and AI.

10,001+

従業員数

Santa Clara

本社所在地

$4.57T

企業価値

レビュー

4.1

10件のレビュー

ワークライフバランス

3.5

報酬

4.2

企業文化

4.3

キャリア

4.5

経営陣

4.0

75%

友人に勧める

良い点

Great culture and supportive environment

Smart colleagues and excellent people

Cutting-edge technology and learning opportunities

改善点

Team-dependent experience and outcomes

Work-life balance issues with long hours

Politics and influence over competence

給与レンジ

73件のデータ

Junior/L3

Mid/L4

Junior/L3 · Analyst

7件のレポート

$170,275

年収総額

基本給

$130,981

ストック

-

ボーナス

-

$155,480

$234,166

面接体験

7件の面接

難易度

3.1

/ 5

体験

ポジティブ 0%

普通 86%

ネガティブ 14%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

System Design Interview

6

Team Review

よくある質問

Coding/Algorithm

System Design

Technical Knowledge

Behavioral/STAR