124 applicants

Company

NVIDIA · 1 week ago

Senior Performance Engineer

California, United States

Full-time

Remote

Senior Level

$148K/yr - $276K/yr

5+ years exp

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Artificial Intelligence (AI)GPU

Growth Opportunities

H1B Sponsor Likely

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Responsibilities

Lead all aspects of implementing performance practices in large scale infrastructure, deliver powerful tools, methodologies, and flows to validate and improve several datacenter products in parallel.

Accelerate strategic customer deployments and ensure speed-of-light bringup and deployment of ground-breaking AI infrastructure by working hand in hand tailoring design and faster processes to customer needs.

Specific responsibilities include owning the architecting of performance design and settings of datacenter at scale products both implemented in FW and SW components to ensure velocity and scale while efficiently using resources. This involves early engagement with HW/FW/SW/platform internal and customer teams, and other groups, to build end-to-end solutions and optimize datacenter product designs.

As a key member you will supply to architecting of the implementation of server and rack level telemetry aspects, collaborate and establish continuous improvements in our design flows.

Participating in engagements with various SW and FW (BMC/SBIOS/OS/drivers etc) teams to develop best-in-class practices and tools, you will be analyzing, debugging and resolving critical firmware and software issues for the best AI workload performance at scale.

Provide engineering solutions to enable large scale performance strategies for performance for Datacenter GPU Computing products and software stacks, ensure technical relationships with internal and external engineering teams, and assisting systems engineers in building creative solutions based on NVIDIA technology.

Be an internal reference for firmware, at scale deployment for datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Accelerated ComputingCUDAC/C++/Python/BashCloud ComputingContainer TechnologyLinux OSHigh Performance ComputingDeep Learning

Required

5+ years of experience in using accelerated computing for datacenter container computing solutions.

Solid understanding of accelerated computing software stacks (CUDA).

Experience using and handling modern Cloud and container-based Enterprise computing architectures.

C/C++/Python/Bash programming/scripting experience.

Experience with CPU architecture.

Background with container technology and Linux based OSes.

Experience working with engineering or academic research community supporting high performance computing or deep learning.

Strong verbal and written communication skills as well as excellent teamwork and communication skills.

Ability to multitask effectively in a dynamic environment.

Action driven with strong analytical and analytical skills with a desire to be involved in multiple diverse and creative projects.

BS in Engineering, Mathematics, Physics, or Computer Science, MS or PhD desirable (or equivalent experience).

Preferred

Deep Learning framework skills.

DL and graph compiling programming skills.

Exposure to virtualization techniques, cloud platform solutions.

Exposure to scheduling and resource management systems.

Experience with large scale HPC environments.

Benefits

Equity and benefits

Company

NVIDIA

Glassdoor

4.6

NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.

Founded in 1993

Santa Clara, California, USA

10,001+ employees

https://www.nvidia.com

H1B Sponsorship

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2023 (735)

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2020 (534)