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Internship Electrical Engineer Nvidia Jobs in Bothell, WA

Nvidia

Senior HPC Cluster Engineer

Redmond, WA

$117K - $160K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Bachelor's degree in Computer Science, Electrical Engineering or related field or equivalent ...

Nvidia

Senior AI Compiler Engineer, MLIR

Seattle, WA

$139K - $183K/yr

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern ... A track record of mentoring early career engineers and interns is a bonus With competitive salaries ...

Nvidia

Senior Software Engineer, AI Networking

Seattle, WA

$139K - $183K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Electrical Engineering or a related science degree (or equivalent experience) * 8+ years of ...

NVIDIA

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

They are seeking a Deep Learning Compiler Engineer to analyze deep learning networks and develop ... and interns is a bonus Company : NVIDIA is a computing platform company operating at the ...

NVIDIA

Senior GPU Supercomputer Scheduler Engineer

Redmond, WA · On-site

$137K - $180K/yr

NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs ... Required : • Bachelor's degree in Computer Science, Electrical Engineering or related field or ...

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Internship Electrical Engineer Nvidia information

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How much do internship electrical engineer nvidia jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for internship electrical engineer nvidia in Bothell, WA is $24.22, according to ZipRecruiter salary data. Most workers in this role earn between $20.43 and $26.88 per hour, depending on experience, location, and employer.

What does an internship electrical engineer do at Nvidia?

An Internship Electrical Engineer at Nvidia assists in designing, testing, and troubleshooting hardware components for advanced computing products such as GPUs and AI systems. Interns may work with cross-functional teams to develop circuit boards, analyze electrical performance, and support prototype builds. They gain hands-on experience with industry-leading technology while learning about Nvidia’s design and manufacturing processes. The role involves using engineering tools, running simulations, and documenting findings to contribute to the development of innovative products.

What kinds of projects do electrical engineering interns typically work on at Nvidia, and how do these projects contribute to the company's goals?

As an Electrical Engineering intern at Nvidia, you can expect to work on hands-on projects that support the development and testing of cutting-edge hardware components, such as GPUs and AI accelerators. Interns often assist in circuit design, schematic review, board bring-up, and validation, collaborating closely with experienced engineers. These projects are integral to Nvidia's mission of advancing high-performance computing and AI technologies, and your contributions can have a direct impact on the performance and reliability of Nvidia’s products. The fast-paced, team-oriented environment encourages learning and skill development while providing valuable industry experience.

What are the key skills and qualifications needed to thrive as an internship electrical engineer at Nvidia, and why are they important?

To thrive as an Internship Electrical Engineer at Nvidia, you need a solid background in electrical engineering principles, circuit design, and familiarity with hardware development, typically supported by enrollment in or recent graduation from an accredited engineering program. Experience with tools such as SPICE simulation, PCB design software (e.g., Altium Designer), and programming languages like Python or C/C++ is highly beneficial. Strong problem-solving abilities, collaboration, and effective communication help interns contribute to team projects and adapt to Nvidia's fast-paced environment. These skills and qualities are crucial for delivering innovative hardware solutions and supporting Nvidia’s cutting-edge technology development.

What are the most commonly searched types of Electrical Engineer Nvidia jobs in Bothell, WA?

The most popular types of Electrical Engineer Nvidia jobs in Bothell, WA are:

What job categories do people searching Internship Electrical Engineer Nvidia jobs in Bothell, WA look for?

The top searched job categories for Internship Electrical Engineer Nvidia jobs in Bothell, WA are:

What cities near Bothell, WA are hiring for Internship Electrical Engineer Nvidia jobs?

Cities near Bothell, WA with the most Internship Electrical Engineer Nvidia job openings:

Internship Electrical Engineer Nvidia jobs near you
Infographic showing various Internship Electrical Engineer Nvidia job openings in Bothell, WA as of August 2026, with employment types broken down into 84% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 94% Physical, 3% Hybrid, and 3% Remote job distribution, with an average salary of $50,376 per year, or $24.2 per hour.

Senior Deep Learning Tools Engineer - CUDA Tile

Nvidia

Redmond, WA

$117K - $160K/yr

Full-time

Re-posted 13 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

NVIDIA is building advanced compiler technologies to accelerate AI workloads, and we are looking for an engineer focused on performance validation, analysis, and tracking. In this role, you will work at the intersection of deep learning compilers, GPU systems, and automation infrastructure, ensuring that performance improvements are measurable, scalable, and continuously validated over time.

Do you want to help drive the performance of next-generation compilers? Are you excited by how GPU performance powers breakthroughs in deep learning, autonomous systems, and high-performance computing? We are seeking a talented Deep Learning Compiler & Tools Engineer focused on CUDA Tile (Performance & Infrastructure) to join our team.

You will collaborate closely with compiler developers, infrastructure providers, and hardware teams to build systems that track, analyze, and improve performance across rapidly evolving AI workloads. If you're passionate about performance, systems, and building infrastructure that drives real-world impact, we want to hear from you.

What You'll Be Doing:

  • Design and develop performance testing frameworks for deep learning compilers and workloads

  • Build and maintain automated pipelines (CI/CD) to continuously track performance across models, hardware, and compiler changes

  • Implement benchmarking systems to measure latency, throughput, and efficiency of AI and HPC workloads

  • Analyze performance trends over time and identify regressions, bottlenecks, and optimization opportunities

  • Partner with compiler and architecture teams to debug and resolve performance issues

  • Develop tools and dashboards for performance visualization, reporting, and insights

  • Enable scalable testing across diverse GPU systems and environments

  • Improve infrastructure to ensure reliable, reproducible, and high-signal performance data

What We Need to See:

  • BS, MS, or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field

  • 5+ years of software engineering experience, including experience in performance engineering, benchmarking, or systems optimization

  • Strong programming skills in Python (C++ is a plus)

  • Experience with CI/CD systems and automation frameworks

  • Familiarity with hardware-aware performance analysis (GPUs, accelerators, or similar systems)

  • Experience working with deep learning frameworks such as PyTorch, TensorFlow, JAX, or TensorRT

  • Background in data analysis, profiling, and regression tracking

  • Ability to debug complex system-level issues across software and hardware layers

Ways to Stand Out from the Crowd::

  • Experience with GPU performance analysis and optimization

  • Understanding of compiler internals (LLVM, MLIR, CUDA compilation flow)

  • Experience building performance dashboards and large-scale telemetry systems

  • Familiarity with hardware/software co-design or low-level performance tuning

  • Experience with distributed testing infrastructure or large-scale benchmarking systems

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered one of the most desirable employers in the technology industry. Our teams are tackling some of the most challenging problems in AI, deep learning, and accelerated computing.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 10, 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.#deeplearning

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

Year founded

1993

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