Senior AI Training Performance Engineer at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Technology, SemiconductorsIndustries

Requirements

PhD (or equivalent experience) in CS, EE or CSEE and 5+ years; or MS and 8+ years of relevant work experience
Strong background in deep learning and neural networks, in particular training
Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture
Proven experience analyzing and tuning application performance
Experience with processor and system-level performance modelling
Programming skills in C++, Python, and CUDA

Responsibilities

Understand, analyze, profile, and optimize AI and deep learning training workloads on state-of-the-art hardware and software platforms
Understand the big picture of training performance on GPUs, prioritizing and then solving problems across many dozens of state-of-the-art neural networks
Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks
Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies
Build tools to automate workload analysis, workload optimization, and other critical workflows

Skills

Key technologies and capabilities for this role

C++PythonCUDAGPU ArchitectureDeep LearningNeural NetworksPerformance AnalysisPerformance OptimizationComputer ArchitecturePerformance Modeling

Questions & Answers

Common questions about this position

What salary is offered for this Senior AI Training Performance Engineer role?

This information is not specified in the job description.

Is this position remote or hybrid?

The position is hybrid.

What are the key qualifications and skills required for this role?

Candidates need a PhD (or equivalent) in CS, EE or CSEE with 5+ years experience, or MS with 8+ years; strong background in deep learning training, understanding of computer architecture and GPU fundamentals, experience in performance analysis and tuning, processor/system performance modeling, and programming in C++, Python, and CUDA.

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

NVIDIA has forward-thinking and hardworking people, is a fast-growing technology company leading the AI revolution, and offers opportunities to impact hardware/software roadmaps while working on industry-leading Deep Learning products.

What makes a strong candidate for this Senior AI Training Performance Engineer position?

Strong candidates are obsessed with performance analysis and optimization, unafraid to work across the hardware/software stack from GPU architecture to Deep Learning Frameworks, passionate about performance, and have experience optimizing AI training workloads.

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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