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Parallel Computing Software Engineer Jobs in California

KLA

Algorithm Software Architecture

Milpitas, CA · On-site

... computing software, setting architectural direction and coaching engineers to deliver scalable ... memory use • Guide parallel and distributed computing patterns (MPI, multi‑GPU scaling ...

Nvidia

Senior Software Engineer - CUDA Driver

Santa Clara, CA · On-site

$143K - $189K/yr

You will join a versatile software engineering team that delivers innovative software features to ... Strong background in parallel computing, preferably writing CUDA programs or CUDA-based libraries.

Nvidia

Senior Fullstack Software Engineer

Santa Clara, CA · Hybrid

$143K - $189K/yr

... parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing ... As a senior software engineer, you will craft highly efficient software to automate and facilitate ...

KLA

Algorithm Software Architecture

Milpitas, CA · On-site

... computing software. The role involves setting architectural direction, mentoring engineers, and ... memory use • Guide parallel and distributed computing patterns (MPI, multi‑GPU scaling ...

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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.

Algorithm Software Architecture

KLA

Milpitas, CA • On-site

Full-time

Re-posted 14 days ago

Job description

Job Summary:
KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. They are seeking a Senior Algorithm Software Architect to lead the design and delivery of GPU-accelerated, high-performance computing software, setting architectural direction and coaching engineers to deliver scalable, reliable systems for large-scale compute and data workflows.
Responsibilities:
• Own the end‑to‑end software architecture for HPC/GPU platforms (services, libraries, data pipelines, deployment)
• Lead technical strategy, decision records, define candidate architectures, lead design reviews and drive decisions; drive clear trade‑offs for performance, reliability, and maintainability
• Design and implement GPU kernels and frameworks (e.g., CUDA, OpenCL, NCCL), optimizing for throughput, latency, and memory use
• Guide parallel and distributed computing patterns (MPI, multi‑GPU scaling, heterogeneous compute)
• Establish performance engineering practices: profiling, benchmarking, regression performance gates (Nsight Systems/Compute, nvprof)
• Collaborate across functions; convert requirements into clear technical plans, roadmaps, and measurable outcomes
• Uphold engineering excellence: coding standards, code reviews, test strategies, observability, security considerations
• Mentor engineers; provide technical leadership on design, delivery, and career growth.
• Communicate architecture, risks, and status to executives and stakeholders with clarity and candor.
Qualifications:
Required:
• 10+ years in software engineering; 5+ years in software architecture for HPC or large-scale systems
• Expert in C++ (17/20) and one scripting language (Python preferred)
• GPU programming expertise (CUDA, OpenCL); strong knowledge of GPU memory hierarchies, streams, occupancy
• Hands-on with parallel/distributed stacks (MPI, NCCL, gRPC) and Linux performance tooling
• Experience with cluster orchestration (Slurm, Kubernetes), CI/CD, and containerization (Docker)
• Track record of technical leadership and exceptional communication with cross-functional teams
• Doctorate (Academic) Degree and related work experience of 3 years; Master's Level Degree and related work experience of 6 years; Bachelor's Level Degree and related work experience of 8 years
Preferred:
• Multi-node, multi-GPU scaling; mixed precision; numerical methods and algorithms
• Experience with H200/H100/A100/L40S-class accelerators and modern profiling workflows
Company:
Kla creates tools and services that promote innovation in the electronics industry. Founded in 1975, the company is headquartered in Milpitas, USA, with a team of 10001+ employees. The company is currently Late Stage.

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