Senior GPU Memory Architect at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Semiconductors, High-Performance ComputingIndustries

Requirements

10+ yrs of experience in CPU/GPU architecture, memory systems design with a focus on energy efficiency in the system
Bachelors in Electrical Engineering, Computer Science, or related field (or equivalent experience)
Expertise in power analysis and modeling in pipeline-based architectures
Good understanding of power analysis tools like Ansys Power Artist, Synopsys PTPX, etc
Experience with C, C++, and some scripting languages

Responsibilities

Develop innovative high-performance processor and system architectures, focusing on the memory system and energy efficiency
Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$
Develop and enhance architecture prototype models for power and noise analysis
Participate in performance and power simulation of features to analyze, define, and improve energy per byte
Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations
Debug power, performance, and functional issues with high-level models, RTL simulation and emulation, silicon, and systems
Collaborate with outside partners on system infrastructure

Skills

Key technologies and capabilities for this role

GPU ArchitectureMemory SystemsPower AnalysisPerformance SimulationPower ModelingRTL SimulationEmulationPPA OptimizationPipeline ArchitecturesEnergy EfficiencyBenchmark Analysis

Questions & Answers

Common questions about this position

What is the base salary range for the Senior GPU Memory Architect position?

The base salary range is 184,000 USD - 356,500 USD, determined based on location, experience, and pay of employees in similar positions.

What benefits are offered for this role?

You will be eligible for equity and benefits.

Is this position remote or does it require office work?

This information is not specified in the job description.

What skills and experience are required for this role?

Required qualifications include 10+ years of experience in CPU/GPU architecture and memory systems design focused on energy efficiency, a Bachelor's in Electrical Engineering, Computer Science, or related field, expertise in power analysis and modeling in pipeline-based architectures, good understanding of power analysis tools like Ansys Power Artist and Synopsys PTPX, and experience with C, C++, and scripting languages.

What makes a candidate stand out for this position?

Candidates can stand out with an MS/PhD in Electrical Engineering, Computer Science, or related field, experience with hardware design languages such as Verilog or VHDL, prior experience developing and optimizing algorithms for power efficiency, demonstrated ability to innovate and drive continuous improvement in system architecture, and excellent communication skills for collaboration.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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