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Internship Opencl Jobs (NOW HIRING)

NVIDIA

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

... OpenCL programming experience • Experiences in systems with constrained resources, such as ... and interns is a bonus Company : NVIDIA is a computing platform company operating at the ...

Apple

SW ML Optimization Engineer

Cupertino, CA · On-site

Experience with GPU or parallel programming-e.g., Metal, OpenCL, CUDA, or similar-through coursework, personal projects, internships, or research. Experience with profiling/performance analysis tools ...

Socket.dev

SW ML Optimization Engineer

Cupertino, CA · On-site

$180 - $240/hr

Experience with GPU or parallel programming--e.g., Metal, OpenCL, CUDA, or similar--through coursework, personal projects, internships, or research. * Experience with profiling/performance analysis ...

New

LRS

Software Engineer, Intern

Waukesha, WI

$23.50/hr

You'll contribute to algorithm development and highperformance computing (GPU/CPU) on Linux, with a focus on C++ and OpenCL. This internship is designed for students who want handson experience ...

Jump Trading

Campus FPGA Engineer (Intern)

Chicago, IL · On-site

$250K/yr

Previous internship experience in hardware or low-level software engineering * Experience with C, C ... HLS or OpenCL * Any programming close to the metal with CPU, GPU, microprocessors, etc. * Linux ...

Jump Trading

Campus FPGA Engineer (Intern)

Chicago, IL

$250K/yr

Previous internship experience in hardware or low-level software engineering * Experience with C, C ... HLS or OpenCL * Any programming close to the metal with CPU, GPU, microprocessors, etc. * Linux ...

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How much do internship opencl jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for internship opencl 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 is the difference between Internship Opencl vs Internship CUDA?

AspectInternship OpenclInternship CUDA
Required CredentialsBasic programming skills, knowledge of parallel computingBasic programming skills, knowledge of parallel computing, some familiarity with NVIDIA hardware
Work EnvironmentCross-platform, supports various hardware vendorsNVIDIA-specific hardware and software environment
Industry UsageUsed in diverse industries for hardware-agnostic parallel processingPrimarily used in industries leveraging NVIDIA GPUs for high-performance computing
Search & Comparison IntentCommonly compared for cross-platform development opportunitiesCompared for NVIDIA-specific GPU development roles

Internship Opencl focuses on cross-platform parallel programming, suitable for various hardware vendors, while Internship CUDA is tailored for NVIDIA GPU development. Both roles require foundational programming skills, but CUDA internships often demand familiarity with NVIDIA hardware. The choice depends on the target hardware environment and industry needs.

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Internship Opencl jobs near you
Infographic showing various Internship Opencl job openings in the United States as of August 2026, with employment types broken down into 10% Internship, 56% Full Time, 32% Part Time, 1% Temporary, and 1% Contract. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.

NVIDIA Spring 2027 Internships: Developer and Performance Technology

Nvidia Corporation

Santa Clara, CA • On-site

$164K/yr

Full-time

Posted 2 days ago

New

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

By submitting your resume, you acknowledge that your 2027 Developer and Performance Technology internship application will be processed in accordance with NVIDIA's Applicant Privacy Policy and you agree to our Terms of Service. We'll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society - from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry-leading Deep Learning teams. We're seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.
Throughout the 8-12-month full-time internship, students will work on projects that have a measurable impact on our business. We're looking for students pursuing a B.S. or M.S. degree within a relevant or related field.
Potential Internships in this field include:
Performance Engineering
  • Running performance, image quality, and power tests for Professional Visualization, AI, and LLM benchmark applications on various GPUs; Configuring computer systems with appropriate hardware and software to run benchmarks
  • Building automation scripts to benchmarking procedure and balancing configuration files; assembling computer hardware, developing and running automation scripts on applications, and designing tools
  • Course or internship experience related to the following areas could be required: Linux and Shell Scripting, GPU Accelerated Deep Learning Frameworks (TRT, Torch, DML), Python, Containers (Docker or Singularity), Embedded Platforms, 3D Graphics, GPU Programming (CUDA, OpenCL), Benchmarking, Image Quality and Power Testing, Scripting, Debugging, Low Level System Configuration (BIOS Configurations, Memory Timing, Controlling Cache Latency, Overclocking)

Platform Performance and Power
  • Completing post-silicon performance and power benchmarking on NVIDIA and competitive GPU products; Compiling and analyzing data for internal software, hardware, sales, and marketing groups to inform decisions
  • Developing, implementing, and maintaining test systems by configuring hardware, operating systems, drivers, and software tools used for benchmarking and data collection; Implementing hands-on tests focused on performance and power for GPU platforms; Maintaining automation tools to improve testing efficiency
  • Course or internship experience related to the following areas could be required: Linux, Python Scripting, Debugging, Electrical Fundamentals (Power Measurement; Multimeters or Data Acquisition Tools), MMs, Agilent DAQs, National Instruments DAQs, GPU Programming (CUDA, OpenCL), Embedded Platforms, Benchmarking, Power Testing

Deep Learning and High-Performance Computing (HPC)
  • Planning and executing GPU performance benchmarking across a wide range of HPC and DL Frameworks and Applications; Aggregating, analyzing, and generating written and visual reports with testing data for internal teams
  • Writing scripts to improve data gathering through automation, designing efficient processes for testing a wide variety of applications and hardware; Assisting with the development of tools and processes to improve performance of automated testing
  • Course or internship experience related to the following areas could be required: GPU-Enabled Deep Learning Frameworks (TensorFlow, PyTorch, MXNet, TensorRT), GPU-Enabled HPC Applications (LAMMPS, GROMACS, Amber, RTM), GPU/CPU Benchmarking (Coud Solutions i.e. AWS, GCP, Azure), GPU Programming (CUDA, OpenACC, OpenCL), Compilers (GNU, Intel Composer, PGI), Clusters (Slurm, Kubernetes)

What we need to see:
  • Must be actively enrolled in a university pursuing a B.S. or M.S. degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, for the full 8-12-month duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered.
  • Developer and Performance Internship Preferred Start Dates: February 2027 or May 2027

Depending on the internship role, prior experience or knowledge requirements could include the following programming skills and technologies:
  • GPU Accelerated Deep Learning Frameworks (TensorFlow, PyTorch, MXNet, TensorRT, Torch, DML), GPU Programming (CUDA, OpenCL), HPC Applications (LAMMPS, GROMACS, Amber, RTM), Linux, Python/Unix Shell Scripting, Containers (Docker or Singularity)
  • 3D Graphics, Image Quality and Power Testing, Low Level System Configuration (BIOS Configurations, Memory Timing, Controlling Cache Latency, Overclocking), Electrical Fundamentals (Power Measurement; Multimeters or Data Acquisition Tools), Compilers (GNU, Intel Composer, PGI), Clusters (Slurm, Kubernetes), Embedded Platforms, Debugging, Benchmarking, Power Testing

Click hereto learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors.
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.
You will also be eligible for Intern benefits.
Applications are accepted on an ongoing basis.
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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