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Remote Cfd Simulation Engineer information

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

To thrive as a Remote CFD Simulation Engineer, you need a strong background in fluid dynamics, numerical methods, and a relevant engineering degree, often supported by experience in computational modeling. Expertise in CFD software tools such as ANSYS Fluent, OpenFOAM, or STAR-CCM+, and familiarity with programming languages like Python or MATLAB, are typically required. Strong problem-solving skills, self-motivation, and effective communication are vital for collaborating remotely and delivering results. These competencies ensure accurate simulations, efficient workflows, and successful project outcomes in a remote engineering environment.

How does a Remote CFD Simulation Engineer typically collaborate with cross-functional teams during projects?

As a Remote CFD Simulation Engineer, you will frequently collaborate with multidisciplinary teams such as design engineers, project managers, and product development specialists. Communication is often handled through virtual meetings, shared documentation platforms, and project management tools to ensure alignment on project goals and timelines. You may participate in regular progress updates, provide simulation results, and offer technical recommendations to influence design decisions. Being proactive in communication and adept at remote collaboration tools is essential for success in this role.

What are Remote CFD Simulation Engineers?

Remote CFD Simulation Engineers are professionals who specialize in using computational fluid dynamics (CFD) software to analyze and solve problems related to fluid flow, heat transfer, and related physical phenomena. They work remotely, often collaborating with engineering teams via digital platforms, to develop simulations for industries such as aerospace, automotive, energy, and manufacturing. Their work helps optimize product designs, improve efficiency, and predict performance without the need for physical prototypes.

What is the difference between Remote Cfd Simulation Engineer vs Remote Mechanical Design Engineer?

AspectRemote Cfd Simulation EngineerRemote Mechanical Design Engineer
Required CredentialsBachelor's or Master's in Mechanical Engineering, CFD certificationsBachelor's or Master's in Mechanical Engineering, CAD certifications
Work EnvironmentSoftware-focused, simulation labs, engineering teamsDesign studios, CAD software, prototyping facilities
Industry UsageAerospace, automotive, energy sectorsManufacturing, product design, consumer goods

Remote Cfd Simulation Engineers primarily focus on fluid dynamics simulations to optimize designs, while Remote Mechanical Design Engineers concentrate on creating and refining mechanical components using CAD tools. Both roles require strong engineering credentials and often work within the same industries, but their daily tasks and tools differ significantly.

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What job categories do people searching Remote Cfd Simulation Engineer jobs in Washington look for? The top searched job categories for Remote Cfd Simulation Engineer jobs in Washington are:
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Remote Cfd 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 11 days ago

SAIC rating

7.8

Company rating: 7.8 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

68th of 203 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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