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Internship Gpu Programming Jobs in California (NOW HIRING)

Samsung Semiconductor, Inc.

Engineer

San Jose, CA

$160K - $208K/yr

Design and document major units in a GPU pipeline targeted at mobile graphics and machine learning ... Completion of a graduate level course, research project, or internship involving the following: 1. ...

Samsung Electronics Co., Ltd.

Engineer

San Jose, CA · On-site

$160K - $208K/yr

Design and document major units in a GPU pipeline targeted at mobile graphics and machine learning ... Completion of a graduate level course, research project, or internship involving the following: 1. ...

Samsung Electronics

Engineer

San Jose, CA · On-site

$160K - $208K/yr

Design and document major units in a GPU pipeline targeted at mobile graphics and machine learning ... Completion of a graduate level course, research project, or internship involving the following: 1. ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... GPU boundaries. • Experience with modern deep learning frameworks (PyTorch or JAX) and runtime compilation. • Robust programming skills in Python and C++. • 4+ years of non-internship ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... GPU boundaries. • Experience with modern deep learning frameworks (PyTorch or JAX) and runtime compilation. • Robust programming skills in Python and C++. • 4+ years of non-internship ...

Hyve Solutions

Hardware Design Engineer

Fremont, CA · Hybrid

$99K - $135K/yr

Experience working on server, storage, AI, GPU, or data center hardware platforms. * Familiarity ... Internship or project experience involving hardware validation and debug. Compensation & Benefits

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Internship Gpu Programming information

What are the key skills and qualifications needed to thrive as an internship in GPU programming, and why are they important?

To thrive as an Internship GPU Programming, you need a solid background in computer science, mathematics, and programming languages such as C++ and Python, often supported by coursework or personal projects in parallel computing. Familiarity with GPU programming frameworks like CUDA or OpenCL and version control systems (e.g., Git) is typically expected. Strong analytical thinking, attention to detail, and effective communication help interns collaborate with teams and troubleshoot complex issues. These skills and qualities are essential for efficiently developing, optimizing, and debugging GPU-accelerated applications in a fast-paced, technical environment.

What types of projects or tasks can an intern expect to work on in a GPU programming internship?

As a GPU programming intern, you can expect to work on tasks such as optimizing existing code for GPU acceleration, developing parallel algorithms using CUDA or OpenCL, and assisting in the profiling and debugging of GPU applications. Interns often collaborate with researchers and software engineers to implement new features or improve the performance of computational workflows. You may also contribute to documentation and testing, gaining exposure to real-world applications in fields like machine learning, scientific computing, or graphics rendering.

What is an internship in GPU programming?

An Internship in GPU Programming is a temporary position, often held by students or recent graduates, where individuals gain hands-on experience working with Graphics Processing Units (GPUs) to develop, optimize, and accelerate software applications. Interns typically work on projects involving parallel computing, machine learning, graphics rendering, or scientific simulations using programming languages such as CUDA or OpenCL. These internships provide an opportunity to learn from experienced engineers, contribute to real-world projects, and develop specialized skills that are valuable in technology and research industries.
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Internship Gpu Programming jobs near you
Infographic showing various Internship Gpu Programming job openings in California as of August 2026, with employment types broken down into 1% Internship, 79% Full Time, 13% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Senior Math Libraries Engineer - Dense Linear Algebra

Nvidia

Santa Clara, CA • Hybrid

$118K - $160K/yr

Full-time

Re-posted 3 days 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.

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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