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Internship Gpu Programming Jobs (NOW HIRING)

Intel

Senior Compiler Engineer

Santa Clara, CA

$149K - $284K/yr

Develop, enhance, test, debug, release, andmaintaincompiler software for Intel's GPU programming ... job experience, internship experience and / or schoolwork/classes/research. The ...

Intel

AI Software Engineering Intern

Folsom, CA

... GPU programming, and performance optimization. Contributes to the design, development, and ... Available to work part-time for 6-12 months and to work onsite for the duration of the internship ...

LRS

Junior Software Engineer Intern

Brookfield, WI

$23.50/hr

... GPU programming technologies such as CUDA and/or OpenCL Familiarity with scripting languages such as Bash or Python Strong foundation in mathematics The pay for this internship position is $23.50 per ...

Intel

AI Software Engineering Intern

Hillsboro, OR

... GPU programming, and performance optimization. Contributes to the design, development, and ... Available to work part-time for 6-12 months and to work onsite for the duration of the internship ...

Intel

GPU Logic Design Engineer

Folsom, CA · On-site

As a GPU Logic Design Engineer, you will play a vital role in developing cutting-edge graphics IPs ... internship experiences and or schoolwork/classes/research. For information on Intel's immigration ...

Intel

GPU Logic Design Engineer

Santa Clara, CA · On-site

As a GPU Logic Design Engineer, you will play a vital role in developing cutting-edge graphics IPs ... internship experiences and or schoolwork/classes/research. For information on Intel's immigration ...

Nvidia

Senior GPU Memory Architect

Austin, TX · On-site

This GPU memory architecture team creates new, innovative products tailored to NVIDIA's world ... Your history of successfully mentoring junior engineers and interns is a huge plus. Ways to stand ...

Nvidia

Senior GPU Memory Architect

Durham, NC · On-site

This GPU memory architecture team creates new, innovative products tailored to NVIDIA's world ... Your history of successfully mentoring junior engineers and interns is a huge plus. Ways to stand ...

Nvidia

Senior GPU Memory Architect

Santa Clara, CA · On-site

This GPU memory architecture team creates new, innovative products tailored to NVIDIA's world ... Your history of successfully mentoring junior engineers and interns is a huge plus. Ways to stand ...

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How much do internship gpu programming jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for internship gpu programming in the United States is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $28.85 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship 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 the United States as of June 2026, with employment types broken down into 5% As Needed, 23% Full Time, 58% Part Time, 12% Contract, and 2% Nights. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $52,867 per year, or $25.4 per hour.

Systems Research Engineer Intern - GPU Programming (Fall 2026)

Together AI

San Francisco, CA • On-site

$58 - $63/hr

Other

Posted 6 days ago

Job description

About The Role

As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

Responsibilities
  • Optimize and fine-tune GPU code to achieve better performance and scalability
  • Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
  • Stay up-to-date with the latest advancements in GPU programming techniques and technologies
Requirements
  • Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
  • Knowledge of ML/AI applications and models
  • Knowledge of performance profiling and optimization tools for GPU programming
  • Excellent problem-solving and analytical skills
Internship Program Details

Our fall internship program spans over 12 to 16 weeks where you'll have the opportunity to work with industry-leading engineers building a cloud from the ground up and possibly contribute to influential open source projects. Our internship dates are September 14th to December 18th. 

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Mamba, FlexGen, Petals, Mixture of Agents, and RedPajama.

Compensation

We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 to $63. Our hourly rates are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

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