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Senior GPU System Performance Architect

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NVIDIA

Aug 2

  • Job
    Full-time
    Entry Level
  • Santa Clara
  • Quick Apply

AI generated summary

  • You should have extensive experience in GPU architecture, performance optimization, system design, and related software tools. Strong analytical skills and a deep understanding of computing systems are essential.
  • You will design, analyze, and optimize GPU system architecture, enhance performance metrics, collaborate with teams, and drive innovation in GPU technologies to meet evolving industry standards.

Requirements

  • Masters or PhD in a relevant field such as Computer Science, Electrical Engineering, or Computer Engineering or equivalent experience
  • 10+ years of relevant work or research experience
  • Strong programming skills in Python and C++ proven throughout your work history
  • Excellent mathematical and analytical skills
  • Work experience that shows a deep knowledge of computer architecture
  • Strong communication, organizational and interpersonal skills with and a real passion for working as a team
  • Experience with analytical performance modeling, simulation, profiling and analysis

Responsibilities

  • Develop innovative processor and system architectures to extend the state of the art in GPU-accelerated cloud computing.
  • You'll analyze trade-offs in system performance, cost and efficiency by developing analytical models, simulators and data visualization tools.
  • Understand and analyze the interactions between hardware and software in large-scale data center deployments of GPU-accelerated systems.
  • Collaborate across the company to guide the direction of GPU-accelerated cloud computing, working with software, product and business teams.

FAQs

What is the job title for this position?

The job title is Senior GPU System Performance Architect.

What are the primary responsibilities of this role?

The primary responsibilities include developing innovative processor and system architectures, analyzing trade-offs in performance and efficiency, understanding hardware-software interactions in GPU-accelerated systems, and collaborating across teams to guide GPU-accelerated cloud computing.

What qualifications are required for this job?

A Master's or PhD in a relevant field, 10+ years of experience, strong programming skills in Python and C++, excellent analytical skills, and deep knowledge of computer architecture are required.

What programming languages should candidates be proficient in?

Candidates should have strong programming skills in Python and C++.

Is experience with analytical performance modeling important for this role?

Yes, experience with analytical performance modeling, simulation, profiling, and analysis is important.

What background can help candidates stand out for this position?

A background in data center/cloud computing design, expertise in data analysis and visualization, and familiarity with GPU computing and parallel programming models can help candidates stand out.

Is NVIDIA an equal opportunity employer?

Yes, NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer.

What is the salary range for this position?

The base salary range is 220,000 USD - 339,250 USD.

Are employees eligible for equity or benefits?

Yes, employees will also be eligible for equity and benefits.

Does the company value diversity in its employees?

Yes, NVIDIA values diversity and does not discriminate on the basis of any protected characteristic.

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NVIDIA

Manufacturing & Electronics
Industry
10,001+
Employees
1993
Founded Year

Mission & Purpose

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.