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Parallel Computing Software Engineer Jobs in California

Allen Control Systems

Staff Software Engineer

Mountain View, CA · On-site

$176K - $294K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Experience with GPU programming, CUDA, OpenCL, parallel computing, or hardware-accelerated software optimization. * Knowledge of networking protocols, distributed systems, edge computing, embedded ...

Luminai

Staff Software Engineer, Product

San Mateo, CA · On-site

$150 - $200/hr

About the Role As a Staff Software Engineer, you will play a foundational role in designing ... Knowledge of parallel computing concepts and distributed systems * Exceptional problem‑solving ...

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Parallel Computing Software Engineer information

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$30.8K

$122.6K

$181.6K

How much do parallel computing software engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for parallel computing software engineer in California is $122,612.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,391.00 and $143,457.00 per year, depending on experience, location, and employer.

What is a parallel computing software engineer?

Parallel Computing Software Engineers are professionals who design, develop, optimize, and maintain software that can run simultaneously on multiple processors or computers. Their work enables applications to process large volumes of data or perform complex computations more efficiently by splitting tasks across multiple processing units. They often use technologies such as multi-threading, distributed computing frameworks, and GPU programming to maximize performance. These engineers are crucial in fields like scientific computing, artificial intelligence, and big data analytics, where processing speed and scalability are essential.

What does a parallel computing software engineer do?

A parallel computing software engineer develops and updates high-performance computing software and tools to increase their efficiency. In this career, you focus on both parallel computing and parallel programming software to solve complex problems or algorithms. More specific duties and responsibilities of this job may revolve around the development of new or improved software to optimize multi-threaded systems or artificial intelligence data. As a parallel computing software engineer, you generally work on a team to build state-of-the-art technology to bring your company's systems to the forefront of the industry. The industries that use parallel computing include engineering, aircraft computing, and government agencies.

What are the key skills and qualifications needed to thrive as a parallel computing software engineer, and why are they important?

To thrive as a Parallel Computing Software Engineer, you need a solid background in computer science, strong programming skills (especially in C/C++ or Python), and expertise in parallel algorithms and data structures, typically supported by a relevant degree. Familiarity with parallel programming frameworks and tools such as MPI, OpenMP, CUDA, and experience working on distributed systems or high-performance computing platforms are essential. Strong problem-solving abilities, teamwork, and effective communication help you to collaborate on complex projects and convey technical ideas clearly. These skills are crucial for building scalable, efficient software solutions that leverage parallelism to maximize computational performance.
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Parallel Computing Software Engineer jobs near you
Infographic showing various Parallel Computing Software Engineer job openings in California as of August 2026, with employment types broken down into 92% Full Time, 4% Temporary, and 4% Contract. Highlights an 87% In-person, and 13% Remote job distribution, with an average salary of $122,612 per year, or $58.9 per hour.

Software Engineer, Parallel Scientific Computing

Vorticity, Inc

Redwood City, CA • On-site

$130K - $190K/yr

Full-time

Posted 8 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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