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Xcelerate Solutions

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Senior GPU Platform Engineer (Linux/CUDA) - TS/SCI

Bethesda, MD · On-site

$134K - $185K/yr

Develop and optimize applications using CUDA or OpenCL, harnessing the full potential of GPU hardware for parallel processing, high-performance computing, and machine learning on Linux platforms.

Viasat

Data Engineer

Germantown, MD · On-site

$115K - $138K/yr

... parallel computing architectures • Experience with scaled data environments and Streaming technologies like Kafka and Spark • Expertise in Scala and/or Java • Working experience in design ...

Via Logic LLC

GPU Software Engineer

Arlington, VA · On-site

$107.90 - $195.05/hr

A solid understanding of GPU programming and parallel computing architectures. * Understanding signal‑processing algorithms written in MATLAB. * Parallelization of existing algorithms.

Leidos

GPU Software Engineer

Arlington, VA · On-site

$107K - $195K/yr

A solid understanding of GPU programming and parallel computing architectures * Understanding signal processing algorithms written in MATLAB * Parallelization of existing algorithms * Decomposing ...

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Parallel Computing information

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 Washington?

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

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

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

Parallel Computing jobs near you
Infographic showing various Parallel Computing job openings in Washington as of August 2026, with employment types broken down into 34% Full Time, and 66% Contract. Highlights an 100% In-person job distribution.

Data Scientist / Data Modeler - SME TS/SCI w/ POLY REQUIRED

Stech Technology UK Limited

Mclean, VA • On-site

$120 - $160/hr

Other

Posted 2 days ago

New

Job description

Data Scientist / Data Modeler – SME

Falls Technology LLC
Location: McLean, VA
Clearance: Active TS/SCI with Polygraph required

Falls Technology is looking for an experienced Data Scientist / Data Modeler SME to join our team supporting a mission-focused data and analytics environment in McLean, VA.

This is a senior, hands-on role focused on large-scale data processing, data modeling, and analytics within clustered computing environments. We’re specifically looking for someone with deep experience using ECL and HPCC Systems, including at least five years of hands-on ECL development experience.

The ideal candidate combines strong data modeling skills with the ability to develop, validate, and implement methodologies for processing and analyzing large, complex datasets.

What You’ll Do
  • Design, develop, and maintain large-scale data processing solutions using ECL and HPCC Systems.
  • Develop and optimize ECL code for high-volume, parallel data processing.
  • Design and evolve data models supporting complex mission and analytic requirements.
  • Analyze large and diverse datasets to identify relationships, patterns, trends, and actionable information.
  • Develop, validate, and implement methodologies supporting analytic requirements within clustered computing environments.
  • Work with analysts, engineers, developers, and mission users to understand data requirements and translate them into technical solutions.
  • Develop processes for transforming, integrating, cleansing, and preparing data for downstream analytics.
  • Evaluate data quality and identify gaps, inconsistencies, and opportunities to improve data usability.
  • Support the development and optimization of scalable data pipelines and processing workflows.
  • Develop supporting tools and analytics using Python, R, SQL, Java, C, or similar technologies as appropriate.
  • Document data models, methodologies, processing logic, and technical solutions.
Required Qualifications
  • Active TS/SCI clearance with Polygraph.
  • Minimum 5 years of hands-on ECL development experience.
  • Strong experience working with HPCC Systems and clustered computing environments.
  • Demonstrated experience designing and implementing data models.
  • Experience processing and analyzing large-scale datasets.
  • Experience developing methodologies and algorithms supporting complex analytic requirements.Experience with parallel or distributed data processing.
  • Experience with one or more of the following:
    • Python
    • R
    • SQL
    • Java
    • C
    • Pig
  • Strong analytical and problem-solving skills.
  • Ability to work directly with technical and mission stakeholders to translate requirements into scalable data solutions.
Desired Qualifications
  • Advanced experience optimizing ECL workloads and HPCC Systems performance.
  • Experience working with complex, highly interconnected datasets.
  • Experience developing reusable data models and analytic frameworks.
  • Experience with entity resolution, relationship analysis, or large-scale data correlation.
  • Experience integrating data from multiple structured and unstructured sources.
  • Experience supporting data science and analytics within mission environments.
  • Experience working with distributed or massively parallel computing architectures.
  • Experience with cloud-based data processing and analytics technologies.
  • Relevant data science, data engineering, cloud, or analytics certifications.
Why Falls Technology

Falls Technology is a small, growing technology company focused on delivering modern software, cloud, data, and analytics solutions for challenging national security missions.

Our size allows our technical people to stay close to the mission and have a meaningful impact on the solutions being built. We’re looking for experienced engineers and data professionals who enjoy solving difficult problems and want their work to matter.

We offer competitive compensation, strong benefits, and the opportunity to work alongside an experienced technical team on challenging mission problems.

Falls Technology LLC is an Equal Opportunity Employer.

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