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Internship Intel Quantum Computing Jobs in California

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Internship Intel Quantum Computing information

What kinds of projects and tasks can I expect to work on during an Intel Quantum Computing internship?

As an intern in Intel's Quantum Computing division, you can expect to work on a mix of hands-on and research-focused projects, such as assisting with the development of quantum algorithms, testing quantum hardware, or contributing to software tools that support quantum research. You will likely collaborate closely with experienced engineers, physicists, and software developers, gaining exposure to both theoretical and practical aspects of quantum technology. Interns often participate in team meetings, present project updates, and have opportunities to learn about the latest advancements in the field. This role is a great way to build foundational skills and network with professionals in the rapidly growing quantum computing industry.

What is an internship Intel Quantum Computing?

Internship Intel Quantum Computing positions are temporary roles offered by Intel for students or recent graduates interested in gaining hands-on experience in quantum computing technologies. These internships typically involve working with Intel's research teams on projects related to quantum hardware, software, and algorithms. Interns may collaborate with engineers and scientists, contribute to cutting-edge research, and participate in developing next-generation quantum computing solutions. The goal is to provide valuable industry experience and exposure to real-world challenges in the rapidly evolving field of quantum computing.

What are the key skills and qualifications needed to thrive as an Intel Quantum Computing intern, and why are they important?

To thrive as an Intel Quantum Computing Intern, you need a solid background in physics, computer science, or electrical engineering, often at the graduate or advanced undergraduate level. Familiarity with programming languages (such as Python or Qiskit), quantum simulation tools, and laboratory instrumentation is highly valued. Strong problem-solving abilities, eagerness to learn, and effective teamwork are essential soft skills for this role. These skills enable interns to contribute meaningfully to advanced research projects and adapt to the rapidly evolving field of quantum technology.
What are the most commonly searched types of Intel Quantum Computing jobs in California? The most popular types of Intel Quantum Computing jobs in California are:
What job categories do people searching Internship Intel Quantum Computing jobs in California look for? The top searched job categories for Internship Intel Quantum Computing jobs in California are:
What cities in California are hiring for Internship Intel Quantum Computing jobs? Cities in California with the most Internship Intel Quantum Computing job openings:
Infographic showing various Internship Intel Quantum Computing job openings in California as of August 2026, with employment types broken down into 8% Internship, 1% As Needed, 65% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution.

Senior Math Libraries Engineer - Dense Linear Algebra

Nvidia

Santa Clara, CA • Hybrid

$118K - $160K/yr

Full-time

Re-posted 8 hours ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies


Job description

We are looking for software engineers to join our development efforts in the area of dense linear algebra kernels for high-performance libraries such as cuSOLVER. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations, using data centers powered by GPUs and high-performance linear algebra libraries. Applications of these technologies include computer aided engineering (CAE), electronic design automation (EDA), quantum chemistry, autonomous vehicles, LLMs, computer vision, encryption, and countless others. Did you know our team develops the GPU accelerated libraries and SDKs that help make these possible?

In this role, you will work together with other developers on designing, developing, and optimizing kernels for various algorithms including triangular factorizations, eigenvalue decompositions and singular value decompositions. Ideal candidates will not only have experience developing accelerated computing kernels, but also be motivated to advance the state-of-the-art in a variety of accelerated computing domains. If this sounds exciting, we would love to meet you!

What you will be doing:

  • Designing, implementing and optimizing scalable high-performance numerical dense linear algebra software on GPUs

  • Providing technical leadership and guidance to library engineers, QA engineers, and interns working with you on projects

  • Working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of libraries

  • Finding and realizing opportunities to improve library quality, performance and maintainability through re-architecting and establishing innovative software development practices

What we need to see:

  • PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience)

  • 5+ years of overall experience in developing, debugging and optimizing high-performance numerical linear algebra software using C++ and parallel programming; ideally using CUDA, MPI, OpenMP, OpenACC, pthreads

  • Strong fundamentals in numerical methods such as computational linear algebra, linear system solvers, and methods for eigenvalue, singular value, and other decompositions

  • Experience developing dense linear algebra libraries such as BLAS, LAPACK; and their parallel counterparts like PBLAS and SCALAPACK

  • Strong collaboration, communication, and documentation habits

Ways to stand out from the crowd:

  • Good knowledge of CPU and/or GPU hardware architecture

  • Experience with adopting and advancing, software development practices such as CI/CD systems and project management tools such as JIRA.

  • Experience with working in a globally distributed organization

  • Strong background of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA)

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing for science and engineering. More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and build our teams with the smartest people in the world! Join us at the forefront of technological advancement.

#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 August 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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