Senior System Architect, GPU

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Full Remote
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Offer summary

Qualifications:

Master's degree in Computer Science, Electrical Engineering, or Computer Engineering with 5+ years of experience., Strong programming skills in C++, C, Perl, and Python, with knowledge of build systems and toolchains., Experience in computer architecture, particularly with Transaction Level Modeling (TLM)., Excellent communication and interpersonal skills, capable of working in a dynamic, distributed team..

Key responsabilities:

  • Architectural design and functional modeling of GPU components and libraries.
  • Define IP boundaries and interface specifications across GPU subsystems.
  • Develop and maintain versioned interface specifications and documentation for ASIC teams.
  • Drive architectural changes for scalable deployment of IP subsystems across multiple GPU families.

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NVIDIA XLarge http://www.nvidia.com
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Job description

A key part of NVIDIA's strength is to innovate how we architect and develop our GPU for the changing AI and accelerated workloads. We are constantly looking for ways to improve the scalability of our design, infrastructure and methodology. We are seeking a motivated system architect with an understanding of architecture, ASIC design and verification flow to help define system architecture. Your role will be cross-disciplinary, working with software, ASIC design, verification, frontend and system architects, and top-level design engineers.

What you will be doing:

  • Architectural design and functional modeling of components in the GPU and commonly used libraries with specific focus on control fabric, Network-on-Chip (NOC), register buses and microcontrollers

  • Define IP boundaries and interface specifications across subsystems within the GPU. Specify coverage and assertion requirements for protocol compliance.

  • Develop versioned interface specification and documentations for architects and ASIC teams. Update and maintain specification for new features, backward compatibility, BFM development, etc

  • Drive key architectural and infrastructural change required for efficient and scalable turnkey deployment of IP subsystems across multiple GPU families or across BUs

  • Develop models, tests, test plans and testing infrastructure for new architectures and features

  • Document decisions in a system architecture specification, working with multi-functional teams in the organization including ASIC design, software, and VLSI to explore architecture trade-offs, define overall solutions and tracking development progress.

What we need to see:

  • Master's degree (or equivalent experience) in a relevant subject area: Computer Science, Electrical Engineering or Computer Engineering with 5+ years of meaningful work experience.

  • Strong programming ability: C++, C, Perl, Python along with a good understanding of build systems (CMAKE, make), toolchains (GCC) and libraries (STL)

  • Computer Architecture background with experience in modeling with Transaction Level Modeling (TLM)

  • Knowledgeable with CPU or GPU architecture especially in graphics and compute pipeline, memory subsystem and/or NOC

  • Strong communication and interpersonal skills are required along with the ability to work in a dynamic, product oriented, distributed team.

The base salary range is 148,000 USD - 287,500 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. 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.

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Experience

Spoken language(s):
English
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Other Skills

  • Social Skills
  • Communication

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