NVIDIASenior HPC Storage Engineer - EDA Infrastructure
NVIDIA is hiring a Senior HPC Storage Engineer - EDA Infrastructure in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on Level.
AI in this role
Research, design, and implement high-performance distributed storage infrastructure to support large-scale deep learning and AI workloads at NVIDIA.
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 PyTorch and TensorFlow.
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 September 21, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.How we rate this
Senior HPC Storage Engineer - EDA Infrastructure at NVIDIA rates 80 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where hpc was part of your work. What did you do?
- Tell me about a project where storage architecture was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where cloud infrastructure was part of your work. What did you do?
- Tell me about a project where performance optimization was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Hpc, Storage Architecture, Distributed Systems, Cloud Infrastructure, and Performance Optimization. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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