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Remote Simulation Engineer Jobs in Virginia (NOW HIRING)

PCT Remote Pilot Operator

Warrenton, VA · Remote

$17.50 - $24/hr

... training simulator. The RPO operates a combination of a simulated radar display and voice ... Experience working in a multidisciplinary team (Multimedia Developers, Quality Assurance ...

... training simulator. The RPO operates a combination of a simulated radar display and voice ... Experience working in a multidisciplinary team (Multimedia Developers, Quality Assurance ...

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 ...

... 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 ...

Senior Data AI Engineer

Alexandria, VA · On-site +1

$103K - $140K/yr

Remote Clearance: Active DoD Secret clearance required Employment Type: Full-Time (W-2) Citizenship ... The platform is a supply chain simulation solution built on Python, FastAPI, and React that enables ...

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

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Payload Subject Matter ... Assess protection capabilities technical performance and modeling and simulation results. Assess ...

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Remote Simulation Engineer information

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

To thrive as a Remote Simulation Engineer, you need a solid background in engineering principles, computational modeling, and a relevant degree in fields like mechanical, electrical, or aerospace engineering. Proficiency with simulation software such as ANSYS, MATLAB, or Simulink, alongside experience with CAD tools, is typically required. Strong problem-solving abilities, self-motivation, and effective remote communication skills help you excel in a distributed work environment. These skills are crucial for delivering accurate, timely simulation results and collaborating efficiently with global teams.

What are Remote Simulation Engineers?

Remote Simulation Engineers are professionals who use computer-based models and simulations to replicate real-world systems, processes, or products, often working from remote locations. They design, develop, and analyze simulations to test and optimize designs in fields such as aerospace, automotive, healthcare, and manufacturing. By leveraging specialized software, they help organizations predict outcomes, reduce costs, and improve efficiency without the need for physical prototypes. Remote Simulation Engineers collaborate with multidisciplinary teams using digital tools, ensuring seamless communication and project delivery. Their role is crucial for organizations aiming to innovate and streamline development in a virtual environment.

What is the difference between Remote Simulation Engineer vs Remote Test Engineer?

AspectRemote Simulation EngineerRemote Test Engineer
Required CredentialsBachelor's or higher in engineering, proficiency in simulation softwareBachelor's or higher in engineering or related field, experience with testing tools
Work EnvironmentDesigning and running simulations, using CAD and simulation platforms remotelyConducting product tests, analyzing results, often remotely or in labs
Industry UsageAutomotive, aerospace, electronics industriesManufacturing, electronics, automotive sectors
Common Search/ComparisonYesYes

The Remote Simulation Engineer focuses on creating and analyzing virtual models to predict product performance, while the Remote Test Engineer conducts physical or virtual tests to validate product quality. Both roles require engineering backgrounds and often overlap in industries like automotive and aerospace, but their core activities differ: simulation versus testing.

How does a Remote Simulation Engineer typically collaborate with on-site teams and stakeholders?

As a Remote Simulation Engineer, you will frequently collaborate with on-site teams, project managers, and other engineers through virtual meetings, cloud-based platforms, and shared simulation tools. Clear communication and proactive coordination are essential, as you may be responsible for explaining simulation results, integrating feedback, and ensuring your models align with real-world requirements. Building strong relationships with cross-functional teams helps bridge the distance and ensures project milestones are met efficiently. Familiarity with collaborative software and version control systems is valuable for seamless teamwork.
What are the most commonly searched types of Simulation Engineer jobs in Virginia? The most popular types of Simulation Engineer jobs in Virginia are:
What job categories do people searching Remote Simulation Engineer jobs in Virginia look for? The top searched job categories for Remote Simulation Engineer jobs in Virginia are:
What cities in Virginia are hiring for Remote Simulation Engineer jobs? Cities in Virginia with the most Remote Simulation Engineer job openings:
Distinguished AI/ML Engineering Lead

Distinguished AI/ML Engineering Lead

Frontier Technology Inc.

Chesapeake, VA • Remote

$99K - $131K/yr

Full-time

Posted yesterday


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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