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 Computer Science, Computer Engineering, Electrical Engineering or equivalent experience
6+ years of relevant meaningful work experience
Strong background in GPU or Deep Learning ASIC architecture for distributed training and/or inference spanning multi-chip/multi-node
Experience with performance modeling, architecture simulation, profiling, and analysis
Solid foundation in machine learning and deep learning, including understanding of modern transformer-based architectures and their performance at scale
Strong programming skills in Python, C, C++

Responsibilities

Develop innovative architectures to extend the state of the art in deep learning performance and efficiency
Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites
Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications
Evaluate PPA (performance, power, area) for hardware features and system level architectural trade-offs
Develop high level simulators in C++/Python
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

PythonC++CGPUDeep LearningPerformance ModelingArchitecture SimulationProfilingPyTorchJAXTensorRTTransformersDistributed TrainingInferenceLLM

Questions & Answers

Common questions about this position

What is the salary range for this Senior Deep Learning Performance Architect position?

The base salary range is 184,000 USD - 356,500 USD, determined based on location, experience, and pay of employees in similar positions. You will also be eligible for equity and benefits.

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

This information is not specified in the job description.

What are the key required skills for this role?

Candidates need an MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent, 6+ years of relevant experience, strong background in GPU or Deep Learning ASIC architecture, experience with performance modeling and analysis, solid foundation in machine learning and deep learning, and strong programming skills in Python, C, C++.

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

NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. The Deep Learning Architecture team focuses on building real-time, efficient computing platforms in the exciting field of AI.

What makes a candidate stand out for this position?

Stand out with background in deep neural network training, inference and optimization in frameworks like Pytorch, JAX, TensorRT, familiarity with advanced optimizations and SW/HW co-design in LLM training and inference, exposure to using AI to accelerate SW engineering, and demonstration of self-motivation and creative/critical thinking.

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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