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Electrical Engineer Nvidia Jobs (NOW HIRING)

Nvidia

DFT Methodology Engineer

Santa Clara, CA

$145K - $191K/yr

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 ... Master's degree (or equivalent experience) in Electrical Engineering or related field with proven ...

Nvidia

Senior CPU Design Engineer

NVIDIA is seeking best-in-class CPU Design Engineers to design the world's leading CPUs. This ... What we need to see: * BS or MS in electrical engineering or computer engineering (or equivalent ...

Nvidia

Test Methodology Engineer

Santa Clara, CA · On-site

NVIDIA has continuously reinvented itself over three decades. Our invention of the GPU in 1999 ... Completion of bachelor's degree or higher in Electrical Engineering/Computer Engineering (or ...

Nvidia

GPU Verification Engineer

Westford, MA · On-site

$141K/yr

NVIDIA is seeking best-in-class ASIC Verification Engineers to verify the world's leading GPUs ... A Bachelor's Degree (or equivalent experience) in Electrical Engineering, Computer Engineering or ...

Nvidia

Senior CPU Design Engineer

OR · On-site +1

NVIDIA is seeking best-in-class CPU Design Engineers to design the world's leading CPUs. This ... Whatweneedtosee: BS or MS in electrical engineering or computer engineering (or equivalent ...

Nvidia

Senior CPU Design Engineer

Westford, MA · Hybrid

NVIDIA is seeking best-in-class CPU Design Engineers to design the world's leading CPUs. This ... Whatweneedtosee: BS or MS in electrical engineering or computer engineering (or equivalent ...

Nvidia

Senior CPU Design Engineer

Hillsboro, OR · Hybrid

NVIDIA is seeking best-in-class CPU Design Engineers to design the world's leading CPUs. This ... What we need to see: * BS or MS in electrical engineering or computer engineering (or equivalent ...

Nvidia

GPU Verification Engineer

Westford, MA

$141K/yr

NVIDIA is seeking best-in-class ASIC Verification Engineers to verify the world's leading GPUs ... A Bachelor's Degree (or equivalent experience) in Electrical Engineering, Computer Engineering or ...

Nvidia

Field Application Engineer, AI Factory

OR · On-site +1

NVIDIA's AI platforms have already made a major impact on the field and are broadly used across ... What We Need To See: BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science ...

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Electrical Engineer Nvidia information

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$111.1K

$168K

How much do electrical engineer nvidia jobs pay per year?

As of Sep 8, 2026, the average yearly pay for electrical engineer nvidia in the United States is $111,091.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $132,000.00 per year, depending on experience, location, and employer.

What is an electrical engineer Nvidia?

An Electrical Engineer at Nvidia is responsible for designing, developing, and testing hardware components for cutting-edge computing and AI technologies. They work on power distribution, high-speed circuit design, PCB layout, and system integration for GPUs, data centers, and autonomous systems. The role requires expertise in circuit design, signal integrity, and industry standards, often involving collaboration with cross-functional teams.

What are the key skills and qualifications needed to thrive as an electrical engineer Nvidia?

To thrive as an Electrical Engineer at Nvidia, you need a solid background in electrical engineering principles, digital and analog circuit design, and a relevant engineering degree. Proficiency with tools like Cadence, SPICE, and knowledge of hardware description languages, as well as familiarity with industry standards and certifications, is highly valued. Exceptional problem-solving skills, teamwork, and effective communication are key soft skills that set candidates apart. These competencies are critical because they ensure you can design innovative hardware, troubleshoot complex issues, and collaborate efficiently on cutting-edge technology projects.

What types of projects and technologies do electrical engineers at Nvidia typically work on?

Electrical Engineers at Nvidia are involved in designing, testing, and optimizing high-performance hardware systems, such as GPUs and AI accelerators, which support a wide range of cutting-edge applications. They work on board-level circuit design, power delivery, signal integrity, and system integration, often collaborating with cross-functional teams including hardware, software, and mechanical engineers. The fast-paced and innovative environment means engineers are continually exposed to new technologies and challenges, allowing for rapid professional growth and hands-on involvement in industry-leading products. This role offers the opportunity to directly influence Nvidia’s hardware platforms that shape advancements in gaming, artificial intelligence, and high-performance computing.

Can I work at NVIDIA as an electrical engineer?

Electrical engineers can work at NVIDIA in roles involving hardware design, circuit development, and system integration. The company often requires relevant experience, proficiency in tools like CAD and simulation software, and a bachelor's or master's degree in electrical engineering or a related field.
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Electrical Engineer Nvidia jobs near you
Infographic showing various Electrical Engineer Nvidia job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 92% Full Time, 5% Part Time, 1% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $111,091 per year, or $53.4 per hour.

Senior High-Performance LLM Training Engineer

Santa Clara, CA • Hybrid

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidiaexternal

Full-time

Re-posted 27 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 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.

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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

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