Senior Storage Performance Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, HPCIndustries

Requirements

12+ years of experience in performance engineering, benchmarking, or HPC/AI systems
Deep expertise in AI/ML and deep learning frameworks (PyTorch, TensorFlow, Triton)
Strong background in storage systems and filesystems
Proven experience with MPI, OpenMP, and Slurm in large-scale compute environments
Proficiency in Python, Bash, and automation frameworks for job orchestration and results parsing
Excellent communication skills; ability to context-switch between deep technical work and high-level business impact
BS, MS, or PhD or equivalent experience in Computer Science, Electrical Engineering, or related field

Responsibilities

Crafting and delivering performance benchmarks across AI, HPC, and enterprise storage platforms
Testing and benchmarking storage appliances (block, file, object) against NVIDIA data center solutions
Operating and adjusting AI inference and training workloads with tools like PyTorch, TensorFlow, and NVIDIA NIMs
Benchmarking and analyzing retrieval-augmented generation (RAG) pipelines, including ingestion, retrieval, and inference performance with vector databases
Profiling and optimizing MPI-based and multi-node distributed applications
Collaborating closely with product managers, system architects, and partners to fine-tune hardware/software stack performance

Skills

Key technologies and capabilities for this role

PyTorchTensorFlowTritonNVIDIA NIMsMPIOpenMPSlurmPythonBashRAGVector DatabasesStorage SystemsFilesystemsHPC

Questions & Answers

Common questions about this position

What is the base salary range for this Senior Storage Performance Engineer role?

The base salary range is 200,000 USD - 322,000 USD, determined based on location, experience, and pay of employees in similar positions. You will also be eligible for equity and benefits.

Is this position remote or does it require working in an office?

This role is based in Santa Clara, CA, suggesting an on-site presence at NVIDIA's location there.

What are the key required skills for this position?

Candidates need 12+ years in performance engineering or HPC/AI systems, deep expertise in AI/ML frameworks like PyTorch and TensorFlow, strong storage systems background, experience with MPI/OpenMP/Slurm, and proficiency in Python/Bash for automation.

What is the company culture like at NVIDIA?

NVIDIA has forward-thinking and hardworking people, values creative and autonomous individuals, and is committed to fostering a diverse work environment as an equal opportunity employer.

What experience will make me stand out as a candidate?

Stand out with experience in RAG pipelines and vector databases like FAISS/Milvus/Qdrant, Kubernetes and CSI-based storage, GPU profiling tools like Nsight Systems, telemetry frameworks like Prometheus/Grafana, and enthusiasm for AI/HPC/storage boundaries.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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