NVIDIA

Technology

SeniorGPUMemoryArchitect

$184–357k Santa Clara, California, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior GPU Memory Architect at NVIDIA. Skills: GPU Memory Architecture, Performance optimization, Silicon design. Develop architecture and micro-architecture. Improve GPU memory system”

What You'll Achieve.

Improve state-of-the-art; Optimize performance; Optimize power efficiency; Optimize complexity; Optimize area; Optimize effort; Optimize schedule

Industry & Context.

Technology
Problems you'll solve

Solving complex problems

What They're Looking For.

Must Have

Master degree or equivalent experience, 6+ years of experience, GPU or CPU Architecture and development, memory caching and interconnects, communication and interpersonal skills, work in a dynamic, product oriented, distributed team

Nice to Have

PhD with a focus in computer architecture, successfully mentoring junior engineers and interns

What You'll Do.

Develop architecture and micro-architecture

Improve GPU memory system

Improve memory management

Optimize power efficiency

Participate in performance simulation

Improve memory access efficiency

Implement high-level models

Maintain high-level models

Analyze application workloads

Analyze performance simulation results

Identify microarchitecture optimizations

Study machine in action

Present experiment results

Propose mechanisms for improvement

Create architectural specifications

Create customer-facing documents

Generate specifications

Debug performance issues

Debug functional issues

How You'll Work.

Team & Collaboration

Product oriented team; Distributed team; Larger group; Industry partners

Communication Scope

Customer-facing documents; Industry specifications

Full Job Description

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 sta

Free ATS check

Applying for this Senior GPU Memory Architect role?

Most applicants get filtered before a human reads their resume. See if yours makes the cut.

How to Apply on Workday

  • Workday has a multi-step form — save your progress after every section.
  • "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
  • Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
  • Job requisition numbers are useful when following up with HR by email.

ANONYMOUS · UNFILTERED

What do employees actually say about NVIDIA?

Real rants from real employees. Read before you apply.

Read Company Rants →