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Nvidia Internship Jobs (NOW HIRING)

Nvidia

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Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For ... Prior internship experience in a related field. * Experience with inference optimization techniques ...

Nvidia

Senior Software Engineer - Agentic Memory

OR · On-site +1

$122K - $161K/yr

NVIDIA's Agentic Memory team is seeking a Senior Software Engineer with experience using ... A history of mentoring junior engineers and interns is a plus. * Candidates with a Master's, Ph.D ...

Nvidia

Senior AI Compiler Engineer, MLIR

Austin, TX

$121K - $160K/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

OR · On-site

$122K - $161K/yr

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern ... A track record of success in mentoring early-career engineers and interns is a bonus. * Track ...

Nvidia

Senior GPU Memory Architect

Austin, TX

NVIDIA is seeking a motivated architect to work with a team in solving complex problems while ... Your history of successfully mentoring junior engineers and interns is a huge plus. Ways to stand ...

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Nvidia Internship information

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How much do nvidia internship jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for nvidia internship in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Nvidia Intern, and why are they important?

To thrive as an Nvidia Intern, you need a strong background in computer science, engineering, or a related field, often demonstrated through coursework and relevant project experience. Familiarity with programming languages such as C++, Python, and experience with GPU computing platforms like CUDA are typically expected. Strong problem-solving abilities, eagerness to learn, and effective teamwork set standout candidates apart. These skills and qualities enable interns to contribute meaningfully to cutting-edge projects and adapt quickly within Nvidia’s innovative and fast-paced environment.

What is an Nvidia Internship?

An Nvidia Internship is a temporary position offered to students and recent graduates who want to gain hands-on experience working at Nvidia, a leading technology company known for its graphics processing units (GPUs) and AI hardware. Interns at Nvidia work on real-world projects alongside experienced professionals in fields such as engineering, software development, research, and more. The program is designed to provide valuable learning opportunities, professional development, and a chance to contribute to cutting-edge technology. Internships typically last for 12 to 16 weeks and are available at various locations worldwide.

What types of projects do Nvidia interns typically work on, and how much ownership do they have over their tasks?

Nvidia interns are often assigned to meaningful projects that align with the company’s core areas such as artificial intelligence, graphics, and hardware engineering. Interns generally work in collaborative teams but are given a significant degree of ownership over their specific tasks, allowing them to make real contributions. Depending on the department, interns may participate in coding, research, data analysis, or hardware testing, and are encouraged to present their progress to team members. This hands-on experience not only builds technical skills but also provides valuable insights into Nvidia’s innovative culture and workflow.

What is the difference between Nvidia Internship vs Nvidia Co-op?

AspectNvidia InternshipNvidia Co-op
DurationTypically 3-6 monthsUsually 6-12 months
Work EnvironmentProject-based, fast-pacedExtended, collaborative projects
CredentialsEnrolled in relevant degree programEnrolled in relevant degree program
PurposeSkill development, explorationDeepening experience, academic credit

Both Nvidia internships and co-ops target students pursuing degrees in relevant fields, offering hands-on experience in a tech environment. Internships are shorter and often more focused on skill-building, while co-ops provide longer-term, in-depth exposure, sometimes with academic credit. The choice depends on your career goals and availability.

What cities are hiring for Nvidia Internship jobs? Cities with the most Nvidia Internship job openings:
Infographic showing various Nvidia Internship job openings in the United States as of May 2026, with employment types broken down into 14% Internship, 1% As Needed, 16% Full Time, 68% Part Time, and 1% Contract. Highlights an 84% Physical, 8% Hybrid, and 8% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
AI and FSI Developer Technology Engineer- New College Grad 2026

AI and FSI Developer Technology Engineer- New College Grad 2026

Nvidia

New York, NY

Full-time

Posted 29 days ago

Job description

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA's GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!

We're looking for an AI Developer Technology Engineer to push the limits of performance at the intersection of AI, high-performance computing, and financial markets. In this role, you'll dive deep into parallel algorithms, GPUs, and complex systems to identify and eliminate bottlenecks, unlocking the full power of the world's most advanced processing hardware. You'll collaborate with top experts across industry and academia, influence next-generation platforms, and share your insights with the global developer community. Would you enjoy solving hard technical problems, love performance tuning, and want your work to have a visible impact across an entire industry? If so, we would love to invite you to consider this role!

What you will be doing:

  • Researching, designing, and developing groundbreaking techniques to accelerate high-performance workloads for FSI-focused, pioneering AI on NVIDIA CPUs and GPUs.

  • Working with leading technical experts to analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.

  • Profiling and eliminating performance bottlenecks across the stack: from algorithms to kernels to system-level behavior.

  • Publishing and presenting your work in conferences, talks, and blogs to educate and inspire the broader developer community.

  • Influencing the design of future hardware architectures, system software, libraries, and programming models by collaborating closely with NVIDIA research, hardware, compiler, and tools teams.

What we need to see:

  • Pursuing or recently completed a Master's or PhD degree (or equivalent experience) in Computer Science, Computer Engineering, or Electrical and Computer Engineering or related field.

  • Relevant work or research experience.

  • Experience with low-level parallel programming (e.g., CUDA).

  • Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.

  • Fluency in C/C++ and solid foundations in algorithms and software design.

  • Experience improving the performance of large-scale computational applications on GPUs.

  • Good understanding of linear algebra.

  • Strong communication and organization skills, with a logical approach to problem solving and solid prioritization abilities.

Ways to stand out from the crowd:

  • Prior internship experience in a related field.

  • Experience with inference optimization techniques and deploying optimized AI models in production.

  • Experience with TensorRT, TensorRT-LLM, and cuTile.

  • Background in capital markets with exposure to systematic/algorithmic strategies or quantitative trading.

  • Experience parallelizing and optimizing machine learning methods such as decision trees, time series models, and Monte Carlo simulations as well as knowledge of financial data models, pricing and risk simulation algorithms, portfolio optimization, or other finance-focused applications and services.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 13, 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

Year founded

1993

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