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Parallel Computing Jobs (NOW HIRING)

Nvidia

Senior GPU Architect

Durham, NC

$125K - $170K/yr

A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly ...

Nvidia

Senior GPU Architect

Santa Clara, CA

$152K - $206K/yr

A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly ...

Nvidia

Senior GPU Architect

Westford, MA

$134K - $182K/yr

A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly ...

Nvidia

Senior GPU Architect

Austin, TX

$128K - $174K/yr

A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly ...

Nvidia Corporation

Senior GPU Architect

Santa Clara, CA · On-site

$152K - $206K/yr

A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for parallel processing algorithms. We are constantly ...

Nvidia

Senior GPU Architect, Deep Learning

Austin, TX · On-site

A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for deep learning and parallel processing algorithms. We ...

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Parallel Computing information

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$25K

$52.4K

$90.5K

How much do parallel computing jobs pay per year?

As of Jul 11, 2026, the average yearly pay for parallel computing in the United States is $52,360.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,000.00 and $59,500.00 per year, depending on experience, location, and employer.

Is parallel computing difficult?

Parallel computing as a job involves designing and implementing systems that perform multiple tasks simultaneously, which requires strong problem-solving skills, knowledge of algorithms, and proficiency with programming tools like MPI or OpenMP. The difficulty depends on the complexity of projects and the individual's experience, but mastering parallel algorithms and debugging concurrent processes can be challenging for beginners. Continuous learning and practical experience are essential for success in this field.

What are the key skills and qualifications needed to thrive as a Parallel Computing Specialist, and why are they important?

To thrive as a Parallel Computing Specialist, you need strong knowledge of computer architecture, parallel algorithms, and experience with programming languages such as C/C++, Python, and frameworks like MPI or OpenMP, often supported by a degree in computer science or a related field. Familiarity with high-performance computing (HPC) environments, GPU programming (CUDA, OpenCL), and cloud-based parallel processing systems is typically required. Analytical thinking, problem-solving abilities, and effective collaboration are crucial soft skills in this role. These skills are vital for efficiently designing, optimizing, and implementing solutions that leverage parallelism to significantly accelerate computational tasks.

What is the highest paying job in computing?

In computing, roles such as Chief Technology Officer (CTO), Solutions Architect, and Data Science Director tend to be among the highest paying, often earning six-figure salaries. Specialized skills in areas like artificial intelligence, cybersecurity, and cloud computing can also command top compensation levels for experienced professionals.

What are some common challenges faced by professionals working in parallel computing roles?

Professionals in parallel computing often encounter challenges such as efficiently dividing complex tasks among multiple processors and minimizing communication overhead between them. Debugging and optimizing performance across parallel architectures can be difficult, as issues like race conditions and load imbalances frequently arise. Additionally, staying current with evolving hardware technologies and parallel programming frameworks is essential to ensure solutions remain efficient and scalable. Collaborating with cross-functional teams, such as data scientists and system architects, is also crucial for integrating parallel solutions into larger projects.

What is the difference between Parallel Computing vs Data Analyst?

AspectParallel ComputingData Analyst
Required CredentialsComputer Science or Engineering degree, programming skillsStatistics, Data Science, or related degree, analytical skills
Work EnvironmentResearch labs, tech companies, high-performance computing centersBusiness, finance, healthcare, corporate offices
Industry UsageTechnology, research, scientific computingBusiness intelligence, market analysis, reporting

While Parallel Computing focuses on developing algorithms to process large data sets efficiently across multiple processors, Data Analysts interpret data to provide actionable insights. Both roles require strong technical skills but serve different purposes: one enhances computational performance, the other informs business decisions.

What is parallel computing?

Parallel computing is a type of computation where many calculations or processes are carried out simultaneously, leveraging multiple processors or computers to solve complex problems more efficiently. It divides large tasks into smaller ones that can be executed concurrently, significantly speeding up processing time. Commonly used in scientific research, data analysis, and engineering, parallel computing is essential for handling large-scale simulations and big data applications.

What engineers make $500,000?

Senior engineers in fields such as software, aerospace, or petroleum engineering can earn $500,000 or more annually, often through a combination of base salary, bonuses, and stock options. High compensation typically requires extensive experience, advanced skills, and working in high-demand industries or leadership roles.

What is an example of parallel computing in real life?

Parallel computing in a job context involves tasks like processing large datasets or simulations simultaneously across multiple processors or cores to improve efficiency. For example, data analysts may use parallel computing tools to analyze big data sets quickly, requiring knowledge of programming languages such as Python or C++ and familiarity with parallel processing frameworks like MPI or OpenMP.
More about Parallel Computing jobs
What cities are hiring for Parallel Computing jobs? Cities with the most Parallel Computing job openings:
What states have the most Parallel Computing jobs? States with the most job openings for Parallel Computing jobs include:
What job categories do people searching Parallel Computing jobs look for? The top searched job categories for Parallel Computing jobs are:
Parallel Computing jobs near you
Research Computing Specialist

Research Computing Specialist

University of North Carolina at Charlotte

Charlotte, NC • On-site

Full-time

Re-posted 9 days ago

The University Of North Carolina At Charlotte rating

6.6

Company rating: 6.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

443rd of 552 rated colleges and universities

Job description

Position Information
General Information
Position Number
001982
Vacancy Open to
All Candidates
Working Title
Research Computing Specialist
Position Designation
EHRA Non-Faculty
Employment Type
Permanent - Full-time
Months per Year
12
Work Schedule
8:00 am - 5:00 pm; Monday - Friday with occasional evening and weekend hours required, as necessary.
Hours per week
40
FLSA Status
Exempt
Division
OneIT
Department
Office of OneIT (Adm)
Work Location
Kennedy
Salary Range
Primary Purpose of Department
The Office of OneIT provides highly reliable information technology infrastructure, tools, and services to empower the University to achieve its academic, research, administrative, and service goals.
The Research Computing team within OneIT provides powerful High Performance Computing services to researchers at the University.
Primary Purpose of Position
This Research Computing Specialist serves as a key team member reporting to the Director of University Research Computing. Critical systems management and other operational duties are performed by this position, with duties, responsibilities, and objectives delegated from the Director. This position contributes to shaping the strategic direction of University Research Computing. At times, this position may provide leadership or supervision of the technical work of the other staff members.
Summary of Position Responsibilities
This position is responsible for supporting ongoing operations of the Research Computing facilities, including systems management and maintenance, developing and deploying upgraded capabilities, and interacting with and supporting users. This position is also responsible for supporting technical design and strategy development. This position may also include the responsibility to direct the technical work of other staff members.
Minimum Education/Experience
  • Bachelor's degree and 4+ years of relevant work experience to include 1-3 years of Linux Systems Administration experience; or
  • An equivalent combination of education and relevant work experience.

Preferred Education, Knowledge, Skills and Experience
  • Experience in High Performance Computing related technologies such as schedulers, parallel computing, storage systems, or scientific applications.
  • Experience specifying, acquiring, and deploying computer hardware and systems software.
  • Experience in Higher Education.
  • 2 to 5 years of Linux Systems Administration experience.

Necessary Certifications/Licenses
Preferred Certifications/Licenses
Special Notes to Applicants
  • If there is a document you feel is relevant to this position that you would like reviewed with your resume and application, you may upload it to the "Other Documents" section of the Applicant Documents.
  • The finalist will be subject to a Criminal Background Check and/or a Motor Vehicle Report.
  • The Search Committee will not contact references without first verifying permission with the finalist.
  • Please ensure your resume reflects the knowledge, skills, abilities, and experiences to support your answers to the supplemental questions.
  • UNC Charlotte Benefits Information: https://hr.charlotte.edu/benefits/benefits-overview/

Posting Open Date
04/03/2026
Posting Close Date
Open Until Filled
Yes
Proposed Hire Date
If time-limited please indicate appointment end date
Contact Information

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