Data Center GPU Performance and TCO Product Analyst 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, High-Performance Computing, Data CentersIndustries

Requirements

5+ years of total experience in technology with previous product management, AI related engineering, design or development experience highly valued
BS or MS or equivalent experience in engineering, computer science, or another technical field (MBA a plus)
Deep understanding of fundamentals of GPU architecture, Machine Learning, Deep Learning, and LLM architecture with ability to articulate relationship between application performance and GPU and data center architecture
Ability to develop intuitive models on the economics of data center workloads including data center total cost of operation and token revenues
Demonstrated ability to fully contribute to above areas within 3 months
Strong desire to learn, motivated to tackle complex problems and the ability to make sophisticated trade-offs
Ways to stand out (Preferred)
2+ years direct experience in developing or deploying large scale GPU based AI applications, like LLMs, for training and inference
Ability to quickly develop intuitive, first-principles based models of Generative AI workload performance using GPU and system architecture (FLOPS, bandwidths, etc.)
Comfort and drive to constantly stay updated with the latest in deep learning research (academic papers) and industry news
Track record of managing multiple parallel efforts, collaborating with diverse teams, including performance engineers, hardware architects, and product managers

Responsibilities

Guide the architecture of the next-generation of GPUs through an intuitive and comprehensive grasp of how GPU architecture affects performance for datacenter applications, especially Large Language Models (LLMs)
Drive the discovery of opportunities for innovation in GPU, system, and data-center architecture by analyzing the latest data center workload trends, Deep Learning (DL) research, analyst reports, competitive landscape, and token economics
Find opportunities where we uniquely can address customer needs, and translate these into compelling GPU value proposition and product proposals
Distill sophisticated analyses into clear recommendations for both technical and non-technical audiences

Skills

GPU Architecture

Data Center

Performance Analysis

Large Language Models

Deep Learning

Product Management

AI Engineering

TCO

Workload Trends

Token Economics

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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