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

Apple

GPU ML Engineer

Cupertino, CA

$150K - $277K/yr

Experience with high performance parallel programming, GPU programming experience Pay & Benefits At Apple, base pay is one part of our total compensation package and is determined within a range.

Synopsys

R&D Engineering, Staff Engineer

Livermore, CA · On-site

$140 - $190/hr

Demonstrated experience with parallel programming using OpenMP and MPI in production codebases * Solid understanding of finite element methods, meshfree methods, or computational dynamics

New

Etched

Inference Software Engineer

Cupertino, CA · On-site

... parallel programming Company : Etched is an AI chip startup that designs and manufactures hardware systems optimized for artificial intelligence model inference workloads. Founded in 2022, the ...

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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:

Parallel Programming jobs near you
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.

Senior AI and Quant DevTech Engineer

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Re-posted 9 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

We are looking for a software engineer with a strong background in parallel processing and GPU architecture to push the limits of performance at the intersection of AI, high-performance computing, and financial markets. In this role, you will dive deep into parallel algorithms, GPUs, and sophisticated systems, identifying and eliminating bottlenecks to unlock the full power of the world's most advanced processing hardware.
You will collaborate with top experts across industry and academia, influence next-generation platforms, and share your insights with the global developer community. Do you enjoy solving hard technical problems, love performance tuning, and want your work to have a visible impact across an entire industry? If so, we'd love for you to consider this role.
What you will be doing:
  • Designing and developing groundbreaking techniques to accelerate high-performance workloads at the intersection of AI, math, and financial systems.
  • Working hands-on with leading technical experts to analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.
  • Profiling and eliminating performance bottlenecks across the stack-from algorithms to kernels to system-level behavior.
  • Publishing and presenting your work in conferences, talks, and blogs to educate and inspire the broader developer community.
  • Influencing the design of future hardware architectures, system software, libraries, and programming models by collaborating closely with NVIDIA research, hardware, compiler, and tools teams.

What we need to see:
  • Strong hands-on experience with CUDA and parallel programming.
  • Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.
  • A Master's or PhD in Computer Science, Computer Engineering, Electrical and Computer Engineering, or a related field.
  • Fluency in C/C++ and a solid foundation in algorithms and software design.
  • 5+ years of relevant work or research experience.
  • Proven experience improving the performance of large-scale computational applications on GPUs.
  • Excellent understanding of linear algebra.
  • Strong communication and organizational skills, with a logical approach to problem-solving and solid prioritization abilities.

Ways to stand out from the crowd:
  • Experience with inference optimization techniques and deploying optimized AI models in production.
  • Experience with TensorRT, TensorRT-LLM, and cuTile.
  • Experience parallelizing and optimizing machine learning methods such as decision trees, time-series models, and Monte Carlo simulations.

#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 9, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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