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Parallel Programming Jobs (NOW HIRING)

Nvidia Corporation

Senior GPU Architect

Santa Clara, CA · On-site

$152K - $206K/yr

Be knowledgeable about future parallel programming models and their impact to hardware. * Develop software for various hardware simulators, test infrastructures or metrics systems including databases.

Nvidia

Senior GPU Architect

Westford, MA

$134K - $182K/yr

Be knowledgeable about future parallel programming models and their impact to hardware. * Develop software for various hardware simulators, test infrastructures or metrics systems including databases.

Nvidia

Senior GPU Architect

Austin, TX

$128K - $174K/yr

Be knowledgeable about future parallel programming models and their impact to hardware. * Develop software for various hardware simulators, test infrastructures or metrics systems including databases.

Nvidia

Senior GPU Architect

Santa Clara, CA

$152K - $206K/yr

Be knowledgeable about future parallel programming models and their impact to hardware. * Develop software for various hardware simulators, test infrastructures or metrics systems including databases.

Nvidia

Senior GPU Architect

Durham, NC

$125K - $170K/yr

Be knowledgeable about future parallel programming models and their impact to hardware. * Develop software for various hardware simulators, test infrastructures or metrics systems including databases.

SourceFly LLC

Systems Engineer

Fort Belvoir, VA · On-site

Proficient in object-oriented programming, multithreaded/parallel programming (OpenMP, CUDA, or OpenCL a plus) * Familiarity with GUI/UI/UX development and networking protocols (REST APIs, WebSocket)

NVIDIA

Senior Software Engineer, NCCL

Santa Clara, CA · On-site

$143K - $189K/yr

NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters. • Participating in and contributing to parallel programming interface specifications like ...

ConfigUSA

CUDA Programmer

Waukesha, WI · On-site

Work with CPU-GPU parallel programming models and optimize data transfer. * Leverage NVIDIA libraries (CUDA, cuBLAS, cuDNN, NCCL as applicable). * Collaborate with system, compute, or AI/ML teams to ...

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Your expertise in GPU computing, performance optimization, and parallel programming will be instrumental in driving the development of high-performance, energy-efficient solutions that redefine the ...

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Your expertise in GPU computing, performance optimization, and parallel programming will be instrumental in driving the development of high-performance, energy-efficient solutions that redefine the ...

Pivotal Solutions

Sr. Software Engineer

Little Rock, AR · On-site

$103K - $136K/yr

Experience with parallel programming and asynchronous patterns * Full stack or n-tier application development in high data volume environments * 10+ years of recent software development experience ...

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Parallel Programming information

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$81K

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How much do parallel programming jobs pay per year?

As of Jun 20, 2026, the average yearly pay for parallel programming in the United States is $110,762.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,500.00 and $119,500.00 per year, depending on experience, location, and employer.

What is a Parallel Programming job?

A Parallel Programming job involves developing software that can execute multiple tasks or computations simultaneously to improve performance and efficiency. Professionals in this field work with multi-core processors, distributed systems, and GPU computing to optimize software for speed and scalability. They typically use programming models like MPI, OpenMP, or CUDA to implement parallelism. Industries such as high-performance computing, data science, and machine learning heavily rely on parallel programming to handle large-scale computations.

What are some typical challenges encountered in a Parallel Programming role?

Professionals in parallel programming often face challenges such as identifying code sections that can be effectively parallelized, managing data dependencies, and handling synchronization between parallel tasks. Debugging and optimizing performance in multi-threaded or distributed environments can also be complex, requiring patience and attention to detail. Collaboration with data scientists, hardware engineers, and other software developers is common, as projects frequently involve cross-functional teamwork. Overcoming these challenges is a rewarding part of the job, leading to faster, more efficient software solutions that can have a significant impact in fields like scientific computing, finance, and machine learning.

What are the key skills and qualifications needed to thrive in the Parallel Programming position, and why are they important?

To excel in Parallel Programming, you need a solid background in computer science, strong proficiency in languages such as C/C++, Python, or Java, and experience with parallel computing frameworks. Familiarity with tools like OpenMP, MPI, CUDA, or parallel processing libraries, as well as relevant certifications or coursework, is highly valuable. Analytical thinking, collaboration, and effective problem-solving are essential soft skills for success in this role. These competencies enable professionals to efficiently develop, debug, and optimize scalable applications in high-performance computing environments.

More about Parallel Programming jobs
What cities are hiring for Parallel Programming jobs? Cities with the most Parallel Programming job openings:
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Parallel Programming jobs near you
Infographic showing various Parallel Programming job openings in the United States as of June 2026, with employment types broken down into 24% Full Time, 62% Part Time, and 14% Contract. Highlights an 74% Physical, 6% Hybrid, and 20% Remote job distribution, with an average salary of $110,762 per year, or $53.3 per hour.
Senior GPU Architect, Deep Learning

Senior GPU Architect, Deep Learning

Nvidia

Durham, NC

Full-time

Posted 16 days ago

Job description

We are now looking for a Senior GPU & Deep Learning Architect!

The NVIDIA GPU Architecture group is looking for world class architects and software developers to join and lead our various architecture efforts. A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for deep learning and parallel processing algorithms. We are constantly looking for ways to improve our GPU architecture, especially for deep learning workloads, both training and inference, and maintain our leadership by developing new parallel programming models, and new architectures required to make this successful. In this position, you will be responsible for developing and enhancing various features in the GPU architecture that advance the state of the art in parallel programming models or parallel computing performance. You would interact with other world-class architects and researchers to build simulators, mapping deep learning workloads to current and future hardware, and validate new architectural features.

What you'll be doing:

  • Design new hardware features for future processing architectures targeted at deep learning workloads, for both training and inference.

  • Advance the state of parallel computation.

  • Be knowledgeable about future parallel programming models and their impact to hardware.

  • Develop software for various hardware simulators, test infrastructures or metrics systems including databases.

  • Work in a team to document, design, develop tools to analyze and simulate, validate, and verify functional or performance models.

  • Develop tests, testplans, and testing infrastructure for new graphics or parallel processing architectures

  • Be hungry to learn and work on simulators, RTL and real silicon.

What we need to see:

  • MS in Computer Science, Electrical Engineering or Computer Engineering or equivalent experience.

  • Experience in working with hardware targeted at deep learning, or working on mapping deep learning algorithms to hardware.

  • 8+ years of relevant industry experience in GPU or other parallel programming architectures (or other equivalent experience).

  • Strong programming ability inC, C++, Perl andPython.

  • Background in computer architecture, parallel processing, signal processing and/or high performance computing.

  • Knowledge of state of the art in DL algorithms and attention mechanisms is a huge plus.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us. If you're creative, autonomous, and love a challenge, consider joining our GPU Architecture team and help us build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly growing field.

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 January 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.
Nvidia logo

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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