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Parallel Programming Jobs in San Jose, CA (NOW HIRING)

Senior GPU Architect

Santa Clara, CA · On-site

$184 - $356.50/hr

We are constantly looking for ways to improve our GPU architecture and maintain our leadership by developing new parallel programming models, new architectures and new infrastructure that is required ...

New

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.

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.

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 ...

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

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

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 ...

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 ...

Senior Software Engineer, NCCL

Santa Clara, CA · On-site

$143K - $189K/yr

Participating in and contributing to parallel programming interface specifications like MPI/OpenSHMEM. * Design, implement and maintain system software that enables interactions among GPUs and ...

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 ...

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Parallel Programming information

See San Jose, CA salary details

$94.9K

$129.8K

$152.4K

How much do parallel programming jobs pay per year?

As of Aug 20, 2026, the average yearly pay for parallel programming in San Jose, CA is $129,812.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,100.00 and $140,100.00 per year, depending on experience, location, and employer.

What is parallel programming?

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 parallel programming, 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.

What are the most commonly searched types of Parallel Programming jobs in San Jose, CA?

The most popular types of Parallel Programming jobs in San Jose, CA are:

What are popular job titles related to Parallel Programming jobs in San Jose, CA?

For Parallel Programming jobs in San Jose, CA, the most frequently searched job titles are:

What job categories do people searching Parallel Programming jobs in San Jose, CA look for?

The top searched job categories for Parallel Programming jobs in San Jose, CA are:

Infographic showing various Parallel Programming job openings in San Jose, CA as of August 2026, with employment types broken down into 1% Internship, 81% Full Time, 13% Part Time, 4% Contract, and 1% Nights. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $129,812 per year, or $62.4 per hour.

Software Engineer, Parallel Scientific Computing

Vorticity Inc.

Redwood City, CA • On-site

$140 - $200/hr

Other

Posted 9 days ago


Job description

We're building a new class of Scientific Processing Units (SPUs) to push the boundaries of High-Performance Computing (HPC). In this role, you'll develop and optimize the core computational kernels needed to run scientific applications across a wide range of domains on our custom parallel SPU architecture, from simulation and emulation to real hardware.

You'll work across abstraction layers. Starting from the mathematics and algorithms behind an application, building high-level reference implementations, translating them into parallel kernels, and optimizing them against our architecture. You should be comfortable moving between a mathematical description of a problem, C++/Python reference code, low-level parallel software, and the hardware that executes it.

This is not an easy role. It requires passion for understanding how hardware and software work together, the ability to wear multiple hats, strong communication skills, a lot of patience, independence, and, most importantly, zero ego. Why? Because this is the first time something like this has ever been attempted.

Responsibilities
  • Develop high-level reference implementations of scientific applications (e.g. finite-difference time-domain methods, computational fluid dynamics, electromagnetic wave propagation, etc.) from mathematical and algorithmic descriptions.
  • Implement and parallelize scientific applications using our proprietary Software Development Kit (SDK) across SPU simulation, emulation, and real-hardware environments.
  • Develop and optimize performance critical kernels for the SPU architecture.
  • Own iterative performance optimization loops, benchmark, profile, identify bottlenecks, implement improvements and repeat, until we reach our performance targets.
  • Understand applications across abstraction layers, from their mathematical formulation to their mapping onto parallel hardware.
  • Identify opportunities to improve our compilation flow, runtime, hardware utilization, and overall system efficiency.
  • Collaborate with architecture and performance teams to analyze bottlenecks and co-design innovative software and hardware solutions.
  • Independently identify problems and opportunities, propose next steps, and drive work forward without requiring detailed task by task direction.
  • Write clear, concise technical documentation for Vorticity’s engineers and customers.
  • Stay current with parallel programming models, High Performance Computing (HPC) architectures, numerical methods, and techniques for mapping scientific workloads onto parallel hardware.
Skills & Qualifications
  • Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or related field.
  • Master's or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or related field.
  • 5+ years of experience in modern C++ (CUDA C++ experience strongly preferred) for parallel programming and high-performance computing. Exceptional candidates with fewer years but strong skills are also welcome.
  • Ability to understand numerical algorithms and translate mathematical descriptions into working implementations. You don't need to be a mathematician, but a gradient, divergence, stencil, or multidimensional discretization should not scare you.
  • Ability and willingness to debug across abstraction layers, from an application or numerical algorithm down through software and into the underlying architecture.
  • Strong understanding of computer architecture and the interaction between software and hardware.
  • Proficiency with C++, Python, and Linux development environments.
  • Excellent written and verbal communication skills.
  • Strong ability to work independently and in a team, while taking ownership of ambiguous problems, and determining what needs to be done next.
  • Willingness to put in the hard work needed to bring our SPU to life.
  • Above all: zero ego.

As passionate scientists and engineers, we are well aware of the plethora of critical problems in the world that cannot be solved because humanity simply does not have enough computing power. To address this, Vorticity is developing a radically new silicon chip architecture and system to dramatically accelerate scientific computing problems.

Vorticity’s mission is to expand human ingenuity. To do that we are building a team of exceptional people to work together on big problems. Join us!

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