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Senior High Performance Computing information

What is the difference between Senior High Performance Computing vs High Performance Computing Engineer?

AspectSenior High Performance ComputingHigh Performance Computing Engineer
CredentialsBachelor's or Master's in Computer Science, often with certifications in HPCBachelor's or Master's in Computer Science or related field, with HPC experience
Work EnvironmentResearch labs, universities, large data centersData centers, research institutions, tech companies
Industry UsageAcademic, research, government projectsCommercial, research, technology sectors
Primary FocusLeadership in HPC projects, strategic planningDesigning, developing, optimizing HPC systems and applications

While both roles involve high-performance computing, Senior High Performance Computing professionals typically focus on leadership and strategic oversight, whereas High Performance Computing Engineers are more involved in technical development and system optimization. The roles often overlap in skills and environment but differ in scope and responsibilities.

What are the most commonly searched types of High Performance Computing jobs in California? The most popular types of High Performance Computing jobs in California are:
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Senior High Performance Computing jobs near you
Senior High-Performance LLM Training Engineer

Senior High-Performance LLM Training Engineer

Nvidia

Santa Clara, CA • Hybrid

Full-time

Posted yesterday

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

We are now looking for a Senior High-Performance LLM Training Engineer!

NVIDIA is seeking experienced engineers specializing in performance analysis and optimization to improve the efficiency of LLM training workloads, which are shaping the world's most advanced computing systems. This position focuses on optimizing NVIDIA's high-performance LLM software stack in frameworks like PyTorch and JAX for high-performance training on thousands of GPUs, while also helping shape hardware roadmaps for the next generation of GPUs powering the AI revolution.

What you will be doing:

  • Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms.

  • Understand the big picture of training performance on GPUs, prioritizing and then solving problems across all 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.

  • Build and support NVIDIA submissions to the MLPerf Training benchmark suite.

  • 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.

What we want to see:

  • PhD in Computer Science, Electrical Engineering or Computer Engineering and 5+ years; or MS (or equivalent experience) and 8+ years of meaningful work experience.

  • Strong background in deep learning and neural networks, in particular training.

  • A deep background in computer architecture and familiarity with the fundamentals of GPU architecture.

  • Proven experience analyzing and tuning application performance & processor and system-level performance modelling.

  • Programming skills in C++, Python, and CUDA.

GPU computing is the most productive and pervasive platform for deep learning and AI. It begins with the most advanced GPUs and the systems and software we build on top of them. We integrate and optimize every deep learning framework. We work with the major systems companies and every major cloud service provider to make GPUs available in data centers and in the cloud. We craft computers and software to bring AI to edge devices, such as self-driving cars and autonomous robots. AI has the potential to spur a wave of social progress unmatched since the industrial revolution.

Widely considered to be one of tech's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. Additionally, this opportunity offers you the ability to collaborate with some of the most forward-thinking and hard-working people in the world, shaping the future of AI in a creative and autonomous work environment that encourages innovation. If you're excited to work across the full hardware & software stack-from GPU architecture to application code-to achieve optimal performance, we want to hear from you!

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 12, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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