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Parallel Computing Jobs in Virginia (NOW HIRING)

Phase2 Technology

Embedded FPGA Engineer

Mclean, VA · On-site

$86K - $198K/yr

Experience with GPU acceleration, parallel computing, or high‑bandwidth data processing. * Experience gathering requirements, shaping development roadmaps, or supporting Agile workflows.

Kepora

Data Scientist

Chantilly, VA

Performing large scale parallel processing of data, and developing, validating, and using methodologies to support analytic requirements in Clustered Computing environments. Required Skills ...

Kepora

Data Scientist

Chantilly, VA · On-site

... scale parallel processing of data, and developing, validating, and using methodologies to support analytic requirements in Clustered Computing environments. Required Skills: 'Ä¢ Demonstrated ...

Booz Allen Hamilton, Inc.

Embedded FPGA Engineer

Mclean, VA · On-site

$131K - $168K/yr

Experience with GPU acceleration, parallel computing, or high-bandwidth data processing * Experience gathering requirements, shaping development roadmaps, or supporting Agile workflows * Experience ...

Booz Allen Hamilton

Embedded FPGA Engineer

Mclean, VA · On-site

$131K - $168K/yr

Experience with GPU acceleration, parallel computing, or highbandwidth data processing * Experience gathering requirements, shaping development roadmaps, or supporting Agile workflows * Experience ...

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Parallel Computing information

See Virginia salary details

$24.8K

$51.9K

$89.7K

How much do parallel computing jobs pay per year?

As of Sep 13, 2026, the average yearly pay for parallel computing in Virginia is $51,911.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,700.00 and $59,000.00 per year, depending on experience, location, and employer.

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 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 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 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.

Is parallel computing hard?

Parallel computing as a job involves designing and managing systems that perform multiple calculations 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 tasks and the level of expertise, but it generally involves understanding concurrency, synchronization, and performance optimization. Gaining experience through coursework, certifications, and hands-on projects can help reduce the learning curve.

What are popular job titles related to Parallel Computing jobs in Virginia?

For Parallel Computing jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Parallel Computing jobs in Virginia look for?

The top searched job categories for Parallel Computing jobs in Virginia are:

Parallel Computing jobs near you
Infographic showing various Parallel Computing job openings in Virginia as of August 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% In-person job distribution, with an average salary of $51,911 per year, or $25 per hour.

Data Scientist

Mclean, VA • On-site

Avid Technology Professionals
IT Services • 51 - 200 employees
Learn more about Avid Technology Professionalsexternal

Full-time

Re-posted just now

Job description

Looking for a Data Scientist to apply and enhance their skills with developing, running, and analyzing results of complex queries against massive scale data stores. The candidate will also increase their skills with the following: · Manipulating high-volume structured and unstructured data to perform analysis and generate reporting/products. · Using analytic techniques and tools and All-Source data analysis to provide technical targeting analytic support to the Sponsor Agency. · Performing large scale parallel processing of data, and developing, validating, and using methodologies to support analytic requirements in Clustered Computing environments.
Required Skills:

• Demonstrated experience with ECL and HPCC (5 years minimum in ECL) • Demonstrated experience using analytic techniques and tools performing technical targeting analytic support for this Sponsor across a spectrum of mission spaces to include applying analytic judgement to data presented. • Demonstrated experience manipulating high-volume structured and unstructured data to perform analysis and generate sound mission relevant analytic reporting/products. • Demonstrated experience using computer languages (e.g., Python, C, SQL) to perform large scale parallel processing of the sponsors data. These languages complement ECL. • Demonstrated experience performing large scale parallel processing of data, and developing, validating, and using methodologies to support analytic requirements in Clustered Computing environments
Desired Skills:
Educational or practical experience in a STEM (Science, Technology, Engineering or Mathematics) field.