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Senior HPC Storage Engineer

NVIDIA

Senior HPC Storage Engineer

NVIDIA

US

·

On-site

·

Full-time

·

4w ago

필수 스킬

Python

Linux

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

As a member of the HW Infrastructure Storage Strategy team, you will provide leadership in the research, design and implementation of ground breaking fast storage solutions to enable runs of demanding high performance computing, and computationally intensive workloads. We seek an expert to identify architectural changes encompassing file, block, and object storage, to cater to the scaling and performance requirements of an expanding cloud infrastructure. As an expert, you will help us with the next-gen storage solutions strategic challenges we encounter with storage design for large scale, high performance workloads, evolving our private/public cloud strategy, capacity modelling, and growth planning across our global computing environment.

What you'll be doing:

  • Research and analyze existing internal distributed storage services.

  • Research, design, and implement scalable, next-gen distributed storage services for HPC workloads, optimizing both performance and cost-effectiveness to meet NVIDIA’s growing infrastructure needs

  • Develop tooling to automate management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.

  • Detail the general procedures and practices, perform technology evaluations, related to distributed file systems.

  • Collaborate across teams to better understand developers' workflows and capture their infrastructure requirements.

  • Influence and guide methodologies for building, testing, and deploying applications to ensure efficient performance and resource utilization.

  • Supporting our researchers to run their flows on our clusters including performance analysis and optimizations of deep learning workflows

  • Root cause analysis and suggest corrective action for problems large and small scales

What we need to see:

  • Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.

  • 8+ years of experience designing and/or operating large scale storage infrastructure.

  • Experience analyzing and tuning storage performance for a variety of workloads.

  • Proficient in Centos/RHEL and/or Ubuntu Linux distros including Python programming and bash scripting

  • In depth understanding of container technologies like Docker, Enroot

Ways to stand out from the crowd:

  • Distributed Storage Expertise: Extensive experience with parallel and distributed filesystems (Ceph, Weka.io, Vast, Lustre, GPFS) and Linux storage kernel development.

  • GPU & AI Infrastructure: Proficient with NVIDIA GPUs, CUDA programming, and NCCL, including performance benchmarking via MLPerf.

  • Hardware & Storage Engineering: Deep familiarity with storage hardware (HDDs, SSDs, NVMe), enclosures, and specialized appliances like Network Appliance.

  • Advanced Networking: Strong background in Software Defined Networking (SDN) and high-performance networking for AI/HPC clusters.

  • Deep Learning Frameworks: Practical experience applying industry-standard frameworks, specifically Py Torch and Tensor Flow.

NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most resourceful and talented people in the world working for us and, due to unprecedented growth, our extraordinary engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

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 for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 26, 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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NVIDIA 소개

NVIDIA

NVIDIA

Public

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

10,001+

직원 수

Santa Clara

본사 위치

$4.57T

기업 가치

리뷰

4.1

10개 리뷰

워라밸

3.5

보상

4.2

문화

4.3

커리어

4.5

경영진

4.0

75%

친구에게 추천

장점

Great culture and supportive environment

Smart colleagues and excellent people

Cutting-edge technology and learning opportunities

단점

Team-dependent experience and outcomes

Work-life balance issues with long hours

Politics and influence over competence

연봉 정보

73개 데이터

Junior/L3

Mid/L4

Junior/L3 · Analyst

7개 리포트

$170,275

총 연봉

기본급

$130,981

주식

-

보너스

-

$155,480

$234,166

면접 경험

7개 면접

난이도

3.1

/ 5

경험

긍정 0%

보통 86%

부정 14%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

System Design Interview

6

Team Review

자주 나오는 질문

Coding/Algorithm

System Design

Technical Knowledge

Behavioral/STAR