Senior High-Performance LLM Training Engineer at NVIDIA

Santa Clara, California, United States

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

PhD in Computer Science, Electrical Engineering, or Computer Engineering and 5+ years of experience; or MS (or equivalent experience) and 8+ years of meaningful work experience
Strong background in deep learning and neural networks, particularly in training
Deep background in computer architecture and familiarity with GPU architecture fundamentals
Proven experience analyzing and tuning application performance and processor/system-level performance modeling
Proficiency in C++, Python, and CUDA

Responsibilities

Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms
Analyze and solve problems across all state-of-the-art neural networks
Implement production-quality software in multiple layers of NVIDIA’s deep learning platform stack (drivers to DL frameworks)
Build and support NVIDIA submissions to the MLPerf Training benchmark suite
Implement key DL training workloads in NVIDIA’s proprietary processor and system simulators for future architecture studies
Build tools to automate workload analysis, optimization, and critical workflows

Skills

Key technologies and capabilities for this role

C++PythonCUDADeep LearningNeural NetworksGPU ArchitectureComputer ArchitecturePerformance AnalysisPerformance TuningMLPerf

Questions & Answers

Common questions about this position

Is this position remote or onsite?

This is an onsite position.

What is the salary for this Senior High-Performance LLM Training Engineer role?

This information is not specified in the job description.

What are the required skills for this role?

The role requires a strong background in deep learning and neural networks (particularly training), deep knowledge of computer architecture and GPU fundamentals, proven experience in performance analysis and tuning, and proficiency in C++, Python, and CUDA.

What is the company culture like at NVIDIA?

NVIDIA offers a creative and autonomous work environment where employees collaborate with forward-thinking individuals to shape the future of AI.

What education and experience are needed to apply?

Candidates need a PhD in Computer Science, Electrical Engineering, or Computer Engineering with 5+ years of experience, or an MS (or equivalent) with 8+ years of meaningful work experience.

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.

Land your dream remote job 3x faster with AI

Try Jobo Free