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Parallel Computing Software Engineer Jobs in California

Nvidia

Senior GPU Architect

Santa Clara, CA · On-site

$152K - $206K/yr

... 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 ...

Nvidia Corporation

Senior GPU Architect

Santa Clara, CA · On-site

$152K - $206K/yr

... 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 ...

Nvidia

Senior GPU Architect

Santa Clara, CA · On-site

$152K - $206K/yr

... 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 ...

ETAP

Senior Software Engineer

Irvine, CA · On-site

$104K - $174K/yr

Job Title: Senior Software Engineer Location: Irvine, CA Job type: Full-time - Hybrid Overview ... Implement data processing architectures, multi-threading or parallel computing techniques, and use ...

Aveva

Senior Software Engineer

Irvine, CA · On-site

$104K - $174K/yr

Job Title: Senior Software Engineer Location: Irvine, CA Job type: Full-time - Hybrid Overview ... Implement data processing architectures, multi-threading or parallel computing techniques, and use ...

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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 Sep 10, 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 September 2026, with employment types broken down into 1% Internship, 1% As Needed, 70% Full Time, 26% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $122,612 per year, or $58.9 per hour.

Software Engineer, SystemML - AI Networking

Menlo Park, CA

Meta
Internet and IT • 10K+ employees
Learn more about Metaexternal

$183K/yr

Full-time

Re-posted 27 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

Job description

In this role, you will be a member of the AI Networking Software team and part of the bigger DC networking organization. The team develops and owns the software stack around NCCL (NVIDIA Collective Communications Library), which enables multi-GPU and multi-node data communication through HPC-style collectives. NCCL has been integrated into PyTorch and is on the critical path of multi-GPU distributed training. In other words, nearly every distributed GPU-based ML workload in Meta Production goes through the SW stack the team owns.At the high level, the team aims to enable Meta-wide ML products and innovations to leverage our large-scale GPU training and inference fleet through an observable, reliable and high-performance distributed AI/GPU communication stack. Currently, one of the team’s focus is on building customized features, SW benchmarks, performance tuners and SW stacks around NCCL and PyTorch to improve the full-stack distributed ML reliability and performance (e.g. Large-Scale GenAI/LLM training) from the trainer down to the inter-GPU and network communication layer. And we are seeking for engineers to work on the space of GenAI/LLM scaling reliability and performance.
Software Engineer, SystemML - AI Networking Responsibilities:
  • Tech-leading the collective communication library development on Meta's large-scale GPU training infra with a focus on GenAI/LLM scaling

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Proven C/C++ and Python programming skills
  • Proven track record of leading successful projects
  • Effective leadership and communication skills
  • Specialized experience in one or more of the following machine learning/deep learning domains: Distributed ML Training, GPU architecture, ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine Learning frameworks (e.g. PyTorch)

Preferred Qualifications:
  • Experience with NCCL and distributed GPU performance analysis on RoCE/Infiniband
  • PhD in Computer Science, Computer Engineering, or relevant technical field
  • Knowledge of GPU architectures and CUDA programming
  • Knowledge of ML, deep learning and LLM
  • Experience with both data parallel and model parallel training, such as Distributed Data Parallel, Fully Sharded Data Parallel (FSDP), Tensor Parallel, and Pipeline Parallel
  • Experience in HPC and parallel computing
  • Experience working with DL frameworks like PyTorch, Caffe2 or TensorFlow
  • Experience in AI framework and trainer development on accelerating large-scale distributed deep learning models

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$183,997/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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