Senior GPU Memory Architect

Posted 6 Days Ago
Be an Early Applicant
3 Locations
In-Office
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Senior GPU Memory Architect will develop memory architecture, perform simulations, analyze performance, define experiments, and create specifications for GPU systems.
Summary Generated by Built In

We are now looking for a Senior GPU Memory Architect.

NVIDIA is seeking a motivated architect to work with a team in solving complex problems while optimizing performance, area, complexity, and power on leading-edge silicon processes. This GPU memory architecture team creates new, innovative products tailored to NVIDIA’s world-changing solutions for autonomous vehicles, AI, gaming, mobile systems.

What you will be doing:

  • Developing architecture and micro-architecture to improve the state-of-the-art in GPU memory system and memory management optimizing along the axes of performance, power efficiency, complexity, area, effort, and schedule.

  • Participating in performance simulation of features to improve memory access efficiency.

  • Implementing and maintaining high-level functional and performance models.

  • Analyzing benchmarks, application workloads and performance simulation results to identify areas for microarchitecture optimizations.

  • Defining and performing experiments to study the machine in action, presenting experiment results to the larger group and proposing mechanisms for improvement.

  • Creating architectural specifications and customer-facing documents. Working with partners in the industry to generate specifications which take into account software interfaces to the GPU.

  • Debugging performance and functional issues with high-level models, RTL simulation, and silicon.

What we need to see:

  • Master degree or equivalent experience in Electrical Engineering, Computer Science, Computer Engineering or related field. A PhD with a focus in computer architecture is a plus.

  • 6+ years of meaningful work experience in GPU or CPU Architecture and development specifically in the area of memory caching and interconnects.

  • Strong communication and interpersonal skills are required along with the ability to work in a dynamic, product oriented, distributed team. Your history of successfully mentoring junior engineers and interns is a huge plus.

Ways to stand out from the crowd:

  • Experience with hardware memory management unit, prefetching, or memory subsystems.

  • Practical experience with multi-core systems and memory coherency.

Do you desire to be a part of a team of talented engineers developing ground-breaking GPU architectures from specification through implementation to extend the state of the art in GPU performance and functionality? Are you motivated to solve complex problems while optimizing performance, area, complexity, and power? If so, our GPU memory architecture group is looking for you. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented market opportunities, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for computer architecture and technology, 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 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 26, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

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.

Skills Required

  • Master's degree or equivalent experience in Electrical Engineering, Computer Science, or related field
  • 6+ years of experience in GPU or CPU architecture development
  • Strong communication and interpersonal skills
  • Experience mentoring junior engineers and interns
  • Experience with hardware memory management unit, prefetching, or memory subsystems
  • Practical experience with multi-core systems and memory coherency

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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