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Parallel Computing Software Engineer Jobs (NOW HIRING)

System Software Engineer - GPU

Santa Clara, CA · On-site

$203K - $240K/yr

We are seeking a System Software Engineer to work on next-generation computing and graphics ... Background with Parallel Computing, PCIE, Nvlink or server product technologies like Infiniband ...

SOFTWARE ENGINEER INTERN Position Summary: The successful candidate will perform research on new ... parallel computing systems CUBRC maintains an Affirmative Action Plan to establish fair access to ...

System Software Engineer - GPU

Santa Clara, CA · On-site

$203K - $240K/yr

We are seeking a System Software Engineer to work on next-generation computing and graphics ... Background with Parallel Computing, PCIE, Nvlink or server product technologies like Infiniband ...

GPU Software Engineer

Arlington, VA · On-site

$107K - $195K/yr

A solid understanding of GPU programming and parallel computing architectures * Understanding ... Build software products that utilize third party mathematics and communication libraries

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Parallel Computing Software Engineer information

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$31.5K

$125.2K

$185.5K

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

As of Jun 24, 2026, the average yearly pay for parallel computing software engineer in the United States is $125,213.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $146,500.00 per year, depending on experience, location, and employer.

What Is the Job of a Parallel Computing Software Engineer?

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 Parallel Computing Software Engineers?

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 are the typical daily responsibilities of a Parallel Computing Software Engineer?

As a Parallel Computing Software Engineer, your daily tasks often include designing, developing, and optimizing algorithms to run efficiently on multi-core processors or distributed systems. You’ll collaborate closely with other software engineers, data scientists, and hardware specialists to ensure applications scale effectively across multiple computing nodes. Debugging and profiling code to identify bottlenecks, maintaining high code quality, and keeping up-to-date with the latest parallel programming models and frameworks are also key parts of the role. Additionally, you may participate in code reviews and help train team members on best practices for parallelism.

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.
What states have the most Parallel Computing Software Engineer jobs? States with the most job openings for Parallel Computing Software Engineer jobs include:
What job categories do people searching Parallel Computing Software Engineer jobs look for? The top searched job categories for Parallel Computing Software Engineer jobs are:
What are popular job titles related to Parallel Computing Software Engineer jobs? For Parallel Computing Software Engineer jobs, the most frequently searched job titles are:
Infographic showing various Parallel Computing Software Engineer job openings in the United States as of June 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $125,213 per year, or $60.2 per hour.
High Performance Computing Software Engineer

High Performance Computing Software Engineer

Zendar

Berkeley, CA

Full-time

Posted 20 days ago


Job description

About Zendar:

Zendar is building perception for physical AI-giving engineers a strong foundation for creating world-class robotics applications. At Zendar, you'll work on perception foundation models that enable robots to understand and interact with their environments across a wide range of industries.
Zendar pioneered RF perception that delivers a vision-like, semantically segmented understanding of the environment-running on embedded automotive systems using only radar data. This RF perception forms the backbone of Zendar's next-generation foundation models, which are built around early fusion of RF and vision data.
This architecture inverts the traditional perception stack. Instead of treating RF signals as secondary, Zendar's models combine vision's high angular resolution with RF's strong temporal and spatial understanding at the earliest stages of perception. The result is a system that sees farther, remains robust to occlusion and adverse weather, and operates far more efficiently than vision-only or lidar-based approaches.

See a demo of Zendar's foundational RF perception
At Zendar, you'll work at the cutting edge of autonomous mobility and robotics-advancing foundation models that will power the next generation of physical AI systems. You'll work with large-scale, real-world, multi-modal datasets composed of synchronized and calibrated radar, camera, and lidar data collected across multiple continents.
Our team brings together deep expertise across hardware, signal processing, machine learning, and software engineering, with decades of experience in sensing and perception. We are a global team with offices in Berkeley, Lindau (Germany), and Paris (France). Zendar is well-funded by leading Tier-1 venture capital firms and has established strong industry partnerships.
Although AI is central to what we build, our hiring process is intentionally human: every resume is reviewed by a real person.

Your Role:

Zendar's Semantic Spectrum perception technology extracts a rich scene understanding from radar sensing, augmented by additional sensors such as IMU and cameras. In addition, Zendar is building an actuation stack on top of its perception outputs. All of these capabilities must run reliably, efficiently, and with deterministic timing on ruggedized embedded platforms suitable for field deployment in the field.

We are seeking experienced software engineers to implement and optimize a high-performance pipeline capable of handling these intensive workloads, leveraging the accelerators available in modern heterogeneous embedded computing platforms. This position is ideal for engineers who are passionate about pushing the limits of modern computer hardware to achieve higher performance, and who are interested in bridging the gap between machine learning research and deployment of AI models on the edge.

It is an exciting opportunity to tackle real-world challenges in bringing algorithms developed in the lab to vehicles operating in diverse physical environments.

What you'll do:

In this role, you will work closely with our researchers to explore the trade-offs between algorithm output quality and its compute efficiency, while creating performance optimized embedded implementations runnable on our production hardware. You will also collaborate with product teams to tackle performance issues encountered in the deployment of our software. To have a thorough understanding of the heterogeneous computing platform we target, you are expected to devise methodologies and microbenchmarks to exercise relevant processing blocks in the system. The knowledge acquired would be incorporated into the evolution of our software system architecture.

What We Look For:

  • Proficiency with modern C++ (we use C++ 17) and python
  • Experience programming multiprocess/multithreaded applications in production environment
  • Experience profiling and analyzing the performance of C++/python applications
  • Experience in optimizing performance for compute intensive workloads on modern computer systems
  • Experience developing for embedded Linux or POSIX systems
  • Familiarity with professional software development tools, such as source control (git), unit testing, and profiling
  • Strong communication and cross-functional collaboration skills

Bonus Points:

  • Experience with developing mission critical software (e.g. aviation or autonomous vehicles)
  • Experience developing software that runs on an RTOS
  • Experience with radar, lidar, cameras, GPS/IMU, or other automotive sensors
  • Experience mentoring team members on software development and best practices
  • Familiarity with CUDA/OpenCL
  • Experience deploying machine learning models in embedded systems

What We Have To Offer:

  • Opportunity to make an impact at a young, venture-backed company in an emerging market
  • Competitive salary from $140-200k depending on experience, benefits and equity
  • Daily catered lunch and a stocked fridge (when working out of the Berkeley, CA office)

Zendar is an equal opportunity employer.

Zendar participates in E-Verify.

Employment Type: FULL_TIME

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About Zendar

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

Berkeley, CA, US

Year founded

2017