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Remote Cfd Simulation Engineer Jobs in Virginia (NOW HIRING)

SAIC

NRO Payload Engineer

Chantilly, VA · Remote

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Payload Subject Matter ... simulation results. • Assess Technology Readiness Levels (TRLs) and identify risks to program ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

... simulations using 3D tools such as PyTorch3D, Unity, or Unreal Engine to train computer vision ... Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning ...

iDirect GOVERNMENT

Senior FPGA Engineer

Herndon, VA · On-site +1

$133K - $171K/yr

This position is based out of our Herndon, VA location with the option of a remote work schedule ... Designing and supporting top-level simulations * Translating requirements into FPGA architectures

GRVTY

Software Engineer, Senior

Herndon, VA · On-site +1

$126K - $166K/yr

What Impact You'll Have GRVTY is looking for a Senior Software Engineer to join a small ... or remote sensing data workflows. * Experience with simulation, modeling, or mission analysis ...

GRVTY

Software Engineer, Senior

Herndon, VA · On-site +1

$126K - $166K/yr

This is hands-on engineering work -- you will be designing and building Python-based software tools ... or remote sensing data workflows. * Experience with simulation, modeling, or mission analysis ...

Pae

Senior Radio Frequency Engineer

Dahlgren, VA · On-site +1

Conduct advanced system modeling and simulations using core RF development methodologies, including ... Classic Reach and Aggregate Remote Capability (ARC). * Finder Family of Systems. * Digital Receiver ...

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Remote Cfd Simulation Engineer information

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 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.

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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Remote Cfd Simulation Engineer jobs near you
Distinguished AI/ML Engineering Lead

Distinguished AI/ML Engineering Lead

Frontier Technology Inc.

Chesapeake, VA • Remote

$99K - $131K/yr

Full-time

Posted 12 days ago

Job description

FTI Defense delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

FTI Defense is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator — designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights.

This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities.


  • Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
  • Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
  • Lead the full AI/ML lifecycle — from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
  • Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
  • Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
  • Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection.
  • Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.
  • Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs.
  • Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse across mission systems.
  • Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.

  • Active Secret clearance required; TS/SCI strongly preferred.
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s or Ph.D. preferred).
  • 10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
  • Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
  • Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
  • Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
  • Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
  • Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable.
  • Experience transitioning R&D systems into accredited production environments.
  • Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.

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