Deep Learning Performance Architect at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI, AutomotiveIndustries

Requirements

Masters or PhD or equivalent experience in relevant discipline (CE, CS&E, CS, AI)
SW Agile skills helpful
Excellent C/C++ programming and software design skills
Python experience a plus
Performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU
GPU programming experience (CUDA or OpenCL) desired
5 years of relevant work experience
Ability to work in a fast-paced customer-oriented team
Excellent communication skills

Responsibilities

Develop highly optimized deep learning kernels for inference
Do performance optimization, analysis, and tuning
Work with cross-collaborative teams across automotive, image understanding, and speech understanding to develop innovative solutions
Occasionally travel to conferences and customers for technical consultation and training

Skills

Key technologies and capabilities for this role

C++PythonCUDAGPU programmingperformance optimizationdeep learningTensorRTprofilingcode optimizationperformance modellingsoftware design

Questions & Answers

Common questions about this position

What is the salary or compensation for this Deep Learning Performance Architect role?

This information is not specified in the job description.

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

This information is not specified in the job description.

What skills are required for this Deep Learning Performance Architect position?

Required skills include excellent C/C++ programming and software design, performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU, and GPU programming experience (CUDA or OpenCL) is desired. Python experience is a plus, and SW Agile skills are helpful.

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

The role involves working in a fast-paced customer-oriented team, collaborating with cross-functional teams across automotive, image understanding, and speech understanding, with occasional travel to conferences and customers. NVIDIA is described as having some of the most brilliant and talented people, valuing creative and autonomous individuals.

What qualifications make a strong candidate for this role?

A Masters or PhD or equivalent experience in a relevant discipline (CE, CS&E, CS, AI), 5 years of relevant work experience, and the key technical skills in C/C++, performance optimization, and GPU programming will make a strong candidate.

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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