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GPU PCIe与启动架构师 - 2027届应届生

雇主

NVIDIA

地点

Santa Clara · 美国

待遇

$面议

工作模式

线下

截止日期

1月6日

福利
Equity, Benefits

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岗位摘要

Design architecture and infrastructure for GPU boot, PCIe/CXL enumeration, and capability discovery,

岗位职责

Our work at
NVIDIA is dedicated towards a computing model focused on visual and AI computing.
For two decades,
NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU.
The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science.
Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world.
We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!
We are looking for a GPU PCIe and Boot Architect to design the architecture and infrastructure for boot, PCIe/CXL enumeration, and capability discovery.
What you’ll be doing:
• As a member of the architecture team, you will be responsible for understanding how the GPU sub-system modules interoperate and interact with overall system
• You will architect and plan features in concert with software, hardware, and verification teams across the globe to implement the next iteration of GPUs
• Create functional and performance models, often in C, along with test plans to validate the features you design
• Actively support post-silicon validation activities What we need to see:
• Pursuing or recently completed a BS or MS in Computer Architecture, Computer Science, or Electrical Engineering (or related degree) or equivalent experience
• Coursework in Computer Architecture, Operation systems, and/or system architecture
• Experience with HW/SW interactions
• Experience building software models, diagnostic tests, and/or directed function and performance tests.
• Strong Proficiency in C (previous project or internship experience is preferred) Ways to stand out from the crowd:
• Knowledge of Advanced interconnects (PCIe, AXI, nvlink, or similar)
• Experience with scripting languages such as Perl
• Understanding of modern security constructs and/or encryption
• Knowledge of RiscV architecture and microcode development
NVIDIA is widely considered to be one of the technology world’s most desirable employers.
We have some of the most brilliant and talented people in the world working for us.
Are you creative and autonomous?
Do you love the challenge of creating the highest performance chips in the industry?
If so, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
The base salary range is 108,000 USD - 178,250 USD for Level 1, and 124,000 USD - 195,500 USD for Level 2.
You will also be eligible for equity and benefits. Applications for this job will be accepted at least until October 10, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.

申请条件

Pursuing or recently completed a BS or MS in Computer Architecture, Computer Science, or Electrical Engineering (or related degree) or equivalent experience.
Coursework in Computer Architecture, Operating Systems, and/or system architecture.
Experience with HW/SW interactions.

雇主简介

NVIDIA is a technology company that designs GPUs and system-on-chip units for gaming, professional visualization, data centers, and automotive markets. The Physics Simulation Team focuses on physics simulation for robotics learning and evaluation.

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数据来源:NVIDIA

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