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Parallel Programming Jobs (NOW HIRING)

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.

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 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.

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 AI

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 ...

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 ...

Synopsys Inc

HPC Software Engineer

Canonsburg, PA · On-site

Responsibilities : • Design, implement, and optimize parallel programming methods within Ansys Mechanical solver products using MPI, GPU programming models like CUDA, HIP, SYCL, OpenMP, and other ...

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 ...

Apple

GPU ML Engineer

Cupertino, CA · On-site

Experience with high performance parallel programming, GPU programming experience Preferred Qualifications Excellent programming and problem-solving skills. Strong communication skills. Strong ...

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 ...

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How much do parallel programming jobs pay per year?

As of Jul 31, 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
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Parallel Programming jobs near you
Infographic showing various Parallel Programming job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, 2% Contract, and 1% Summer. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $110,762 per year, or $53.3 per hour.

GPU Systems Engineer - HPC / Parallel Computing

Vast.ai Inc

San Francisco, CA • On-site

$160K - $320K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 7 days ago

Job description

About Us
Vast.ai's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing-reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.
About the Role
We're looking for a systems engineer with HPC or parallel programming experience to help scale AI inference. You'll leverage your knowledge of high-performance systems to optimize GPU performance at the bleeding edge of AI.
  • Full-Time
  • On-site at either our SF or LA offices
Tech Stack
CUDA/C++, GPGPU, Python, Linux
Key Responsibilities
  • Design and optimize GPU kernels and tensor libraries
  • Translate HPC techniques into scalable AI inference solutions
  • Evaluate emerging architectures and resource management approaches
  • Collaborate with technical leadership to improve GPU infrastructure efficiency
Ideal Experience
  • Advanced C++ (C++17/20 preferred)
  • Expertise with at least one parallel framework (CUDA, HIP, SYCL, OpenCL, OpenACC, or similar)
  • Strong background in systems optimization and HPC performance tooling
  • Familiarity with distributed training/inference frameworks (bonus)
Interview Process
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
  • Initial screening (virtual, 15 minutes)
  • Quick dive into Vast, systems and architectures (virtual, 30 minutes)
  • LLM-assisted coding assessment (virtual, 1 hour)
  • Meet and greet with coding assessment (on-site, 2 hours)

Our goal is to complete the interview process in two weeks.
Benefits
  • Comprehensive health, dental, vision, and life insurance
  • 401(k) with company match
  • Meaningful early-stage equity
  • Onsite meals, snacks, and close collaboration with founders/tech leaders
  • Ambitious, fast-paced startup culture where initiative is rewarded

Apply