Senior Applied Power Architect - GPU at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Automotive, Gaming, MobileIndustries

Requirements

MSEE/MSCE, preferably PhD, or equivalent experience with a specialization in low-power-processor architectures
Strong knowledge of energy efficient system design fundamentals and related tradeoffs from 6+ years of relevant industry experience
Deep understanding of processors (GPU is a plus), servers, and system-SW architectures, and their performance/power modeling techniques
Proficiency with Python and data analysis packages like Pandas, NumPy, PyTorch
Exposure to industry standard Power Analysis EDA tools such as PrimePower (a plus)
Experience with performance monitors/simulators used in modern processor architectures
Exposure to lab setup including power measurement equipment such as scope/DAQ, and ability to analyze board-level power issues like supply voltage, over-current (helpful)
Strong interpersonal and organizational skills and the ability & desire to work as a great teammate

Responsibilities

Inventing flows/methodologies and building the power estimation models/tools for GPU products and AI systems such as NVIDIA DGX/HGX as well as Graphics cards and MaxQ notebooks
Investigate multi-die technologies and come up with innovative solutions to address packaging, interconnect, physical design, electrical and thermal challenges
Drive performance vs power analysis to enable management/marketing with meaningful product decisions and customer interaction
Collaborate closely with other System/SW Architects, Signal Integrity/Packaging experts and Product engineers to understand product challenges and energy efficiency improvements

Skills

Python

Pandas

NumPy

PyTorch

PrimePower

Power Estimation

GPU Architecture

Performance Modeling

System Architecture

Data Analysis

Multi-Die Technologies

Signal Integrity

Packaging

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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