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Remote Modeling Simulation Engineer information

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$40.3K

$127.6K

$196.9K

How much do remote modeling simulation engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for remote modeling simulation engineer in Silver Spring, MD is $127,567.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $151,400.00 per year, depending on experience, location, and employer.

What is the difference between Remote Modeling Simulation Engineer vs Remote Data Analyst?

AspectRemote Modeling Simulation EngineerRemote Data Analyst
Required CredentialsBachelor's or higher in engineering, computer science, or related fields; experience with simulation softwareBachelor's or higher in statistics, mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentEngineering teams, simulation labs, software development settingsBusiness, finance, healthcare, or tech companies analyzing data sets
Industry UsageManufacturing, aerospace, automotive, defenseFinance, marketing, healthcare, technology
Common Search/ComparisonYesYes

The Remote Modeling Simulation Engineer focuses on creating and running simulations to predict system behaviors, often in engineering or manufacturing contexts. In contrast, the Remote Data Analyst interprets data to inform business decisions across various industries. While both roles require analytical skills and technical knowledge, their tools, applications, and industry focus differ significantly.

How does a Remote Modeling Simulation Engineer typically collaborate with cross-functional teams despite working remotely?

Remote Modeling Simulation Engineers frequently work with multidisciplinary teams, including software developers, project managers, and subject matter experts. Collaboration is typically facilitated through virtual meetings, shared simulation platforms, and cloud-based project management tools. Regular communication and thorough documentation are essential to ensure alignment on project goals and simulation requirements. While remote work offers flexibility, it also requires proactive engagement to stay connected and effectively contribute to team-driven problem solving.

What are Remote Modeling Simulation Engineers?

Remote Modeling Simulation Engineers are professionals who use computer-based models and simulations to analyze, design, and optimize systems or products, often working from a location outside of a traditional office. They leverage specialized software to create virtual prototypes and run simulations, which helps in testing and improving designs without the need for physical experiments. These engineers collaborate with teams online, and their work is crucial in industries such as aerospace, automotive, energy, and manufacturing. Their remote setup allows companies to tap into a wider talent pool and offers professionals greater flexibility.

What are the key skills and qualifications needed to thrive as a Remote Modeling Simulation Engineer, and why are they important?

To thrive as a Remote Modeling Simulation Engineer, you need a solid background in engineering or computer science, strong mathematical modeling skills, and experience with simulation methodologies. Familiarity with tools like MATLAB, Simulink, Python, and simulation software, along with relevant certifications such as Certified Systems Engineering Professional (CSEP), is often required. Exceptional problem-solving, self-motivation, and clear communication are crucial soft skills, especially when collaborating remotely with diverse teams. These skills ensure accurate model development, effective virtual teamwork, and the delivery of reliable simulation results for complex engineering challenges.
What are the most commonly searched types of Modeling Simulation Engineer jobs in Silver Spring, MD? The most popular types of Modeling Simulation Engineer jobs in Silver Spring, MD are:
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What job categories do people searching Remote Modeling Simulation Engineer jobs in Silver Spring, MD look for? The top searched job categories for Remote Modeling Simulation Engineer jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Remote Modeling Simulation Engineer jobs? Cities near Silver Spring, MD with the most Remote Modeling Simulation Engineer job openings:
Remote Modeling Simulation Engineer jobs near you
Machine Learning Modeling and Simulation Engineer

Machine Learning Modeling and Simulation Engineer

SAIC

Chantilly, VA • On-site, Remote

Full-time

Posted 22 days ago

SAIC rating

7.8

Company rating: 7.8 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

71st of 204 rated it services

Job description

Job ID: 2611773

Location: Chantilly, VA, US

Date Posted: 2026-04-22

Category: Engineering and Sciences

Subcategory: Modeling/Sim Engr

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS.SCI_wPoly

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_ON_SITE


Description

SAIC has need for a Machine Learning Modeling and Simulation Engineer  to support a rapidly expanding Government Intelligence Community (IC) customer with cutting-edge programs within the National Reconnaissance Office (NRO) in Chantilly, VA.

Note:  The role offers a flexible work schedule, but we ask our team to be available for team meetings during core business hours (10:00 a.m. – 3:00 p.m.).

As the Machine Learning Modeling and Simulation Engineer, you will provide technical expertise across a variety of Machine Learning (ML) and Modeling and Simulation (M&S) topics, including developing and training ML models, designing simulation frameworks, conducting performance analyses, and applying data-driven approaches to solve complex problems. You will also assist with Systems Engineering topics (e.g., requirements, configuration management, readiness, verification and validation, etc.) to ensure seamless integration of ML capabilities within simulation environments. 

Job Duties to include:

  • Develop and maintain physics-based simulation models of spacecraft systems, including structures, sensors, and mission environments.
  • Perform end-to-end performance modeling for satellite missions, integrating sensor, orbital, and environmental models.
  • Conduct sensor phenomenology studies, including optical, infrared, or radar modeling for detection, tracking, and signature analysis.
  • Perform orbital mechanics modeling including orbit determination, orbital maneuvering, and spacecraft flight dynamics.
  • Use scripting languages (Python, MATLAB, or similar) to automate workflows, perform data analysis, and interface between simulation tools.
  • Apply Artificial Intelligence/Machine Learning (AI/ML) techniques (e.g., supervised/unsupervised learning, reinforcement learning, predictive modeling) to enhance simulation fidelity and performance.
  • Develop AI/ML models to analyze and predict satellite system behaviors, performance metrics, and mission outcomes based on simulation data.
  • Design and implement algorithms for anomaly detection, predictive maintenance, and optimization of satellite operations.
  • Use statistical and machine learning techniques to analyze data, identify patterns, and uncover insights relevant to satellite systems.
  • Integrate AI/ML models into existing simulation frameworks and tools to enhance their capabilities.
  • Provide value-added judgment and offer strategic recommendations to the customer on program objectives, advanced technologies, and system enhancements. 
  • Produce highly detailed, practical, and consistent deliverables that align with the organization’s mission and objectives, with a focus on innovation and cutting-edge solutions in machine learning and simulation. 

Qualifications

Required Education and Experience:

  • Bachelor's Aerospace Engineering, Mechanical Engineering, Physics, and five (5) years or more experience; Masters and three (3) years or more experience; PhD and 0 years related experience. 
  • Active Top Secret/SCI w/Poly Clearance.
  • 3+ years of experience in modeling and simulation for aerospace or space systems.
  • Strong understanding of sensor phenomenology --such as optical, infrared, or radar systems --and associated modeling methods.
  • Intermediate Python programming experience, demonstrated through hands-on experience with tasks such as data manipulation, automation, and development of Python-based solutions. Experience with libraries such as NumPy, SciPy, pandas, and matplotlib is beneficial.
  • Ability to communicate technical results clearly in written and verbal formats.

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