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Remote Supercomputer Jobs in Virginia (NOW HIRING)

Remote Supercomputer information

What is a remote supercomputer?

Remote supercomputers are powerful computing systems that can be accessed and operated over the internet or a network, rather than requiring physical presence at their location. These systems allow researchers, scientists, and engineers to run complex simulations, analyze large datasets, and perform high-performance computations from anywhere in the world. Remote access to supercomputers is typically managed through secure protocols, specialized software, and user authentication to ensure data security and efficient resource allocation. This setup enables collaboration across institutions and accelerates scientific discovery by making advanced computational resources more widely available.

What skills and qualifications are needed to work with remote supercomputers?

To thrive as a Remote Supercomputer Operator, you need expertise in high-performance computing (HPC), system administration, and a relevant degree in computer science or engineering. Familiarity with operating systems like Linux, cluster management tools (e.g., SLURM), and parallel programming frameworks is typically required. Strong problem-solving, attention to detail, and effective communication skills set top operators apart. These competencies are crucial for maintaining system uptime, optimizing performance, and supporting users in complex computational environments.

What are common challenges faced by professionals working with remote supercomputers, and how can they be addressed?

Professionals working with remote supercomputers often encounter challenges such as network latency, data transfer bottlenecks, and the need for efficient job scheduling. To address these, it's important to familiarize yourself with optimized data management practices and use appropriate file transfer tools. Additionally, collaborating closely with system administrators and leveraging user support resources can help resolve technical issues quickly. Staying updated on best practices and system upgrades is also key to maintaining productivity in this dynamic environment.

What is the difference between Remote Supercomputer vs Remote Data Scientist?

AspectRemote SupercomputerRemote Data Scientist
Required CredentialsAdvanced degrees in computer science, high-performance computing certificationsDegree in data science, statistics, or related fields; certifications like CAP or Microsoft Certified Data Scientist
Work EnvironmentAccess to high-performance computing clusters, specialized hardwareData analysis platforms, cloud services, programming environments
Industry UsageResearch institutions, scientific computing, large-scale simulationsTech companies, finance, healthcare, marketing analytics
Common Search/ComparisonHigh-performance computing roles, supercomputing jobsData analysis roles, machine learning jobs

Remote Supercomputers focus on managing and utilizing high-performance computing resources for complex simulations and research, requiring specialized technical skills. Remote Data Scientists analyze large datasets using statistical and machine learning techniques, often leveraging cloud platforms. While both roles involve advanced technical expertise, they serve different industry needs and environments.

What are the most commonly searched types of Supercomputer jobs in Virginia?

The most popular types of Supercomputer jobs in Virginia are:

What job categories do people searching Remote Supercomputer jobs in Virginia look for?

The top searched job categories for Remote Supercomputer jobs in Virginia are:

What cities in Virginia are hiring for Remote Supercomputer jobs?

Cities in Virginia with the most Remote Supercomputer job openings:

Infographic showing various Remote Supercomputer job openings in Virginia as of July 2026, with employment types broken down into 85% Full Time, 11% Part Time, and 4% Contract. Highlights an 60% Physical, 3% Hybrid, and 37% Remote job distribution.

Artificial Intelligence/Machine Learning Engineer (AI/ML)

SAIC

Chantilly, VA • On-site, Remote

$100K - $200K/yr

Full-time

Retirement

Posted 17 days ago


SAIC rating

7.9

Company rating: 7.9 out of 10

Based on 79 frontline employees who took The Breakroom Quiz

80th of 226 rated it services


Job description

Job ID: 2615646

Location: Chantilly, VA, US

Date Posted: 2026-08-13

Category: Engineering and Sciences

Subcategory: Modeling/Sim Engr

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS.SCI

Clearance Level Must Be Able to Obtain: TS/SCI with Poly

Potential for Remote Work: ORA_ON_SITE


Description

SAIC is seeking an AI/ML Engineer to join our team conducting a wide variety of analyses in support of Government satellite programs in Earth orbits. Areas of work may include:

  • Recognizing different types of satellites based on observations of them using optical and radar sensors
  • Scheduling space surveillance sensors to collaboratively find, recognize and track maneuvering satellites
  • Deciding what activities satellites should undertake

Satellite designers and operations planners will leverage your analyses to inform critical decisions. As part of an agile team including experts in astrodynamics, sensors and AI/ML you will collaboratively simulate operations concepts at-scale with support from our cloud computing and supercomputing specialists. You can expect regular opportunities to meet with and optionally present findings to local senior government customers.

  • Use programming languages such as Python, C++, or others to leverage existing analysis tools and develop new ones
  • Conduct independent trade studies and technical assessments
  • Review and validate algorithms and results provided by external teams
  • Develop and optionally present actionable technical briefings

Salary range: $100,000 – $200,000, based on qualifications listed below, plus company 401(k) match and discounted employee stock purchase plan

Flexible schedule: On-site core collaboration hours from 10 am to 3 pm, options to work nine or eight days out of every two weeks

Stability: Our team supports a fully-funded prime contract with the government.  Additionally, our analysts routinely support other prime contracts as-necessary.  As a large company with a major presence in Northern Virginia, SAIC offers a broad array of work opportunities for employees locally as well as nationally

Growth and career progression: You will have access to mentoring by experts in AI/ML and many other fields. Senior staff will have opportunities to serve as principals and team leaders.  Managers will maintain open communications to ensure that you thrive

Detailed AI/ML job description:

  • Conduct Exploratory Data Analysis (EDA) to identify patterns for feature engineering
  • Design, develop, and evaluate machine learning algorithms, including supervised, unsupervised, and reinforcement learning
  • Build, train, and tune predictive models using state-of-the-art frameworks and tools
  • Collaborate with cross-functional teams to identify challenges, define problems, and translate them into actionable AI/ML solutions
  • Implement and optimize algorithms for tasks such as anomaly detection, prediction, classification, optimization, clustering, and natural language processing
  • Deploy machine learning models into production environments and establish pipelines for scalability and monitoring
  • Analyze model performance and identify opportunities for improvement by leveraging testing strategies and tuning hyperparameters

Qualifications

Required:

  • Education degree: Computer Science, Data Science, Applied Math, or a related technical field
  • Education and minimum professional experience for start of salary range: Bachelor’s plus two years, Master’s plus zero years, or PhD plus zero years
  • Experience: Astrodynamics
  • Programming: Python, C++, MATLAB, or similar
  • Clearance: Minimum of TS/SCI, should have current or be able to pass polygraph test

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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