Senior Deep Learning Performance 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

Artificial Intelligence, Semiconductors, High-Performance ComputingIndustries

Requirements

MS or PhD in a relevant discipline (Computer Science, Electrical Engineering, Computer Engineering, etc) or equivalent experience
4+ years of experience in parallel computing architectures, interconnect fabrics and deep learning applications
Background in GPU or Deep Learning ASIC architecture evaluation for training and/or inference
Strong programming skills in Python and C++

Responsibilities

Develop innovative HW architectures to extend the state of the art in parallel computing performance, energy efficiency and programmability
Benchmark and analyze AI workloads in single and multi-node configurations
Develop high level simulator and analysis tools in C++/Python
Evaluate PPA (performance, power, area) for hardware features and system-level architectural trade-offs
Work closely with peer architecture teams and product management to guide development of the products
Keep abreast with emerging trends and research in deep learning

Skills

Key technologies and capabilities for this role

PythonC++GPU ArchitectureDeep LearningParallel ComputingComputer ArchitectureInterconnect FabricsASICTransformer ModelsAI BenchmarkingPPA Analysis

Questions & Answers

Common questions about this position

What is the base salary range for this position?

The base salary range is 184,000 USD - 287,500 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 a remote position or does it require working in an office?

This information is not specified in the job description.

What are the required qualifications and skills for this role?

Candidates need an MS or PhD in a relevant discipline or equivalent experience, 4+ years in parallel computing architectures, interconnect fabrics and deep learning applications, background in GPU or Deep Learning ASIC architecture evaluation, and strong programming skills in Python and C++.

What makes a candidate stand out for this position?

Stand out with solid fundamental knowledge in computer architecture and interconnect fabrics, understanding of modern transformer-based model architectures, ability to simplify and communicate technical concepts to non-technical audiences, and a curious demeanor with excellent problem-solving skills.

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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