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, High-Performance ComputingIndustries

Requirements

Masters Degree (or equivalent experience) and 6+ years of meaningful relevant experience or PhD and 3+ years of experience in Computer Science, Electrical Engineering, Computer Engineering, or related field
Strong foundation in Deep Learning model architectures and performance tradeoffs
Experience with performance and energy modeling, power architecture, architecture simulation, profiling, analysis, and visualizations
Strong programming skills in Python, C, C++
Experience with the architecture of, or workload analysis on, DL accelerators

Responsibilities

Develop innovative architectures to extend the state of the art in deep learning performance and efficiency
Prototype key deep learning algorithms and applications
Analyze performance, cost and energy trade-offs by developing analytical models, simulators and test suites
Characterize power and performance on silicon parts and translate the learnings to architecture features and simulators
Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications
Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

Skills

Key technologies and capabilities for this role

PythonCC++CUDAPyTorchJAXDeep LearningPerformance ModelingEnergy ModelingArchitecture SimulationProfilingGPU Computing

Questions & Answers

Common questions about this position

What is the base salary range for this position?

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

Is this role remote or does it require working from an office?

This information is not specified in the job description.

What are the required skills for this Senior Deep Learning Performance Architect role?

Candidates need a Masters Degree (or equivalent) with 6+ years or PhD with 3+ years in relevant fields, strong foundation in Deep Learning model architectures and performance tradeoffs, experience with performance and energy modeling, power architecture, architecture simulation, profiling, analysis, and visualizations, and strong programming skills in Python, C, C++.

What is the company culture like at NVIDIA for this team?

NVIDIA offers highly competitive salaries and a comprehensive benefits package, and is widely considered one of the technology world’s most desirable employers. The Deep Learning Architecture team focuses on building real-time, cost-effective computing platforms in an exciting and rapidly growing field.

What makes a candidate stand out for this role?

Background with GPU Computing and parallel programming models such as CUDA, along with experience with deep neural network training, inference and optimization in leading frameworks like Pytorch or JAX, will help candidates stand out.

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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