Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
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  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
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  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.
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Nvidia Principal Infrastructure Performance and Development Engineer in Santa Clara, California

Joining NVIDIA's AI Efficiency Team means contributing to the infrastructure that powers our leading-edge AI research. This team focuses on optimizing efficiency and resiliency of ML workloads, as well as developing scalable AI infrastructure tools and services. Our objective is to deliver a stable, scalable environment for NVIDIA's AI researchers, providing them with the necessary resources and scale to foster innovation. We're transforming the way Deep Learning applications run on tens of thousands of GPUs. Join our team of experts and help us build a supercharged AI platform that maximizes efficiency, resilience, and Model FLOPs Utilization (MFU). In this position you will be collaborating with a diverse team that cuts across many areas of Deep Learning HW/SW stack in building a highly scalable, fault tolerant and optimized AI platform.

What you will be doing:

  • Build tools and frameworks that provide real time application performance metrics that can be correlated with system metrics

  • Develop automation frameworks that empower applications to thoughtfully predict and overcome system/infrastructure failures, ensuring fault tolerance.

  • Collaborate with software teams to pinpoint performance bottlenecks. Design, prototype, and integrate solutions that deliver demonstrable performance gains in production environments.

  • Adapt and enhance communication libraries to seamlessly support innovative network topologies and system architectures.

  • Design or adapt optimized storage solutions to boost Deep Learning efficiency, resilience, and developer productivity.

    What We Need to See:

  • BS/MS/PhD (or equivalent experience) in Computer Science, Electrical Engineering or a related field.

  • Proven experience in least one of the following area:

    10+ years of experience in analyzing and improving performance of training applications using PyTorch or similar framework 10+ years of experience with building distributed software applications 10+ years of experience in building storage solutions for Deep Learning applications 10+ years of background in building automated fault tolerant distributed applications 5+ years building tools for bottleneck analysis and automation of fault tolerance in distributed environments.

  • Strong background in parallel programming and distributed systems

  • Experience analyzing and optimizing large scale distributed applications.

  • Excellent verbal and written communication skills

    Ways To Stand Out From The Crowd:

  • Deep understanding of HPC and distributed system architecture with emphasis on RDMA

  • Hands on working experience in more than one of the above areas especially with performance analysis and profiling of Deep Learning workloads.

  • Comfortable navigating and working with the PyTorch codebase.

  • Proven understanding of CUDA and GPU architecture

The base salary range is 272,000 USD - 419,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits (https://www.nvidia.com/en-us/benefits/) . NVIDIA accepts applications on an ongoing basis.

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.

NVIDIA is a Learning Machine

NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and the metaverse is transforming the world's largest industries and profoundly impacting society.

Learn more about NVIDIA .

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