Senior HPC Storage Engineer

NVIDIA Ltd.
Santa Clara, CA, United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$184,000.0 - $356,500.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Bash Shell Ubuntu (Operating System) CentOS Cloud Computing Nvidia CUDA Computer Programming Computer Networks Computer Graphics Linux Distributed File Systems Distributed Data Store
+17 more
General Parallel File Systems Networking Hardware Python (Programming Language) Linux Kernel Red Hat Enterprise Linux Tensorflow AI Infrastructure Ceph (Software) Graphics Processing Unit (GPU) High Performance Computing Pytorch Deep Learning Containerization Storage Technologies Information Technology Docker Nvme

Job description

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

Requirements

  • 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, * 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 PyTorch and TensorFlow.

Benefits & conditions

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:12 min

Addressing the competitive landscape of specialized hardware demands

Hazal Mestci +1 · Coffee With Developers

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

52 sec

Running persistent Linux environments directly on Windows

Ben Breard Ben Breard · WWC 2025

2:08 min

History and scale of NVIDIA GPU computing

Paul Graham Paul Graham · LIVE

2:34 min

Docker sandbox architecture and microVM environment integration

Manuel de la Peña Manuel de la Peña · WWC Europe 2026

3:55 min

Demonstrating .NET installation on Debian and Azure Linux

Silvano Coriani Silvano Coriani · Europe 2026 Virtual

Videos

See all

Related articles

See all