Datacenter GPU Power Architect at NVIDIA

Santa Clara, California, United States

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$108,000 – $212,750Compensation

Junior (1 to 2 years), Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, HPC, SemiconductorsIndustries

Requirements

MSEE/MSCE, or equivalent experience with 2+ years of experience related to Power / Performance estimation and optimization techniques
Knowledge of energy-efficient chip design fundamentals and related tradeoffs
Familiarity with low-power design techniques such as multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS)
Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques
Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch
Familiarity with performance monitors/simulators used in modern processor architectures

Responsibilities

Contributing to power estimation models and tools for GPU products and systems like NVIDIA DGX/HGX based datacenters
Early GPU & System Architecture exploration with a focus on energy efficiency and Total Cost of Ownership (TCO) improvements at the GPU and Datacenter level
Performing Performance vs. Power Analysis and tracking ASIC milestones for impactful NVIDIA future product lineups
Deploying machine learning techniques to develop highly accurate power and performance models of GPUs, CPUs, Switches, and platforms
Understanding workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements
Modeling & analysis of cutting-edge technologies like high-speed & high-density interconnects

Skills

Key technologies and capabilities for this role

PythonPandasNumPyPyTorchGPU ArchitecturePower ModelingPerformance AnalysisDVFSClock GatingPower GatingMachine Learning

Questions & Answers

Common questions about this position

What is the salary range for the Datacenter GPU Power Architect position?

The base salary range is $108,000 - $212,750 USD.

Is this a remote or hybrid role?

This is a hybrid position.

What skills and experience are required for this role?

Requirements include MSEE/MSCE or equivalent with 2+ years in power/performance estimation, knowledge of energy-efficient chip design and low-power techniques like multi-VT and DVFS, understanding of processors and system-SW, and proficiency in Python with Pandas, NumPy, PyTorch.

What is the company culture like at NVIDIA?

NVIDIA fosters a diverse work environment, is committed to equal opportunity, and is considered one of the technology world’s most desirable employers, leading in AI, HPC, and visualization.

What benefits are offered for this position?

Benefits include equity and benefits.

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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