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Model Engineering Jobs in Virginia (NOW HIRING)

Minimum Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field ... Strong understanding of model evaluation metrics (e.g., precision, recall, F1) and statistical ...

Provide independent effective challenge to model developers, owners, and users and assess whether identified model risks are appropriately understood, documented, and mitigated. * Evaluate model ...

Structural Modeler Engineer

Reston, VA · On-site

$75K - $125K/yr

... Modeler Engineer to support on-going research and development efforts and develop new business in ... Conduct reverse engineering. * Engineer precise load calculations, system sizing, and performance ...

Showing results 41-60

Model Engineering information

See Virginia salary details

$10

$31

$66

How much do model engineering jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for model engineering in Virginia is $31.10, according to ZipRecruiter salary data. Most workers in this role earn between $18.85 and $38.85 per hour, depending on experience, location, and employer.

What is model engineering?

Model engineering is the discipline of designing, building, and testing scale models of machines, engines, and mechanical systems, often as a hobby or for educational purposes. It involves applying engineering principles to create functional replicas, usually of steam engines, locomotives, or other mechanical devices. Model engineers use skills in machining, metalworking, and problem-solving to bring detailed plans to life. The field combines creativity, craftsmanship, and technical knowledge, and is popular among enthusiasts who enjoy both the process and the finished models.

What are the key skills and qualifications needed to thrive as a model engineer, and why are they important?

To thrive as a Model Engineer, you need a solid background in mechanical engineering principles, precision fabrication, and often a relevant engineering degree or technical training. Familiarity with CAD software, CNC machines, lathes, and other fabrication tools is typically required, along with any relevant safety certifications. Attention to detail, creativity, and strong problem-solving skills help set outstanding model engineers apart. These skills ensure that accurate, functional, and high-quality models or prototypes are produced efficiently and safely.

What are some typical challenges faced by model engineers when collaborating with cross-functional teams?

Model engineers often work closely with data scientists, product managers, and software engineers to develop and deploy machine learning models. A common challenge is ensuring clear communication across teams with different technical backgrounds, especially when translating complex model requirements into actionable development tasks. Additionally, balancing accuracy and performance with business needs can be demanding, requiring model engineers to find practical solutions that align with project goals. Regular meetings and thorough documentation are essential to streamline collaboration and overcome these hurdles.

What is the difference between Model Engineering vs Mechanical Engineering?

AspectModel EngineeringMechanical Engineering
CredentialsTypically requires specialized training or certifications in model making and designRequires a bachelor's degree or higher in mechanical engineering or related fields
Work EnvironmentHobbyist workshops, small-scale manufacturing, or specialized model shopsIndustrial facilities, engineering firms, manufacturing plants
Industry UsageUsed in hobbyist communities, model railroads, and small-scale prototypesApplied across various industries including automotive, aerospace, and manufacturing

Model Engineering focuses on creating detailed, small-scale models often as a hobby or for prototypes, requiring specialized skills and certifications. Mechanical Engineering covers a broad range of industrial applications, involving design, analysis, and manufacturing of mechanical systems. While both involve mechanical principles, Model Engineering is more specialized and hobby-oriented, whereas Mechanical Engineering is a comprehensive, industry-wide profession.

What does a model engineering do?

A model engineer designs, builds, and maintains detailed scale models, often of machinery, vehicles, or architectural structures. They use skills in drafting, machining, and assembly, frequently working with tools like lathes and CNC machines in workshops or labs. Model engineers may also create technical drawings and ensure models meet precise specifications.

What are popular job titles related to Model Engineering jobs in Virginia?

For Model Engineering jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Model Engineering jobs in Virginia look for?

The top searched job categories for Model Engineering jobs in Virginia are:

Infographic showing various Model Engineering job openings in Virginia as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $64,686 per year, or $31.1 per hour.

AI Model Engineer with Security Clearance

Fairfax, VA • On-site

$125K - $150K/yr

Other

Posted 8 days ago


Key responsibilities

  • Design, train, implement, and maintain end-to-end machine learning algorithms and their pipelines.

  • Evaluate emerging AI/ML technologies, conduct rapid feasibility studies, and develop prototypes to support mission-critical objectives.

  • Provide technical leadership and strategic guidance on AI/ML integration, ensuring secure, compliant, and efficient AI operations.


Job description

Job Description Everforth ECS is seeking an AI Model Engineer to work in a hybrid remote/onsite capacity, with minimum of 3 business days onsite at our Fairfax, VA corporate office and/or our Ashburn, VA customer site. Please note: This position is contingent upon contract award Everforth ECS is seeking an accomplished AI/ML Engineer to provide technical leadership and strategic guidance on the integration of advanced artificial intelligence and machine learning solutions to support mission-critical government and defense objectives. The ideal candidate is innovative with a track record of evaluating, experimenting with, and transitioning emerging technologies into operational use. This role requires exceptional communication skills, strong technical expertise, and experience collaborating across the Department of Homeland Security (DHS) and other government agencies. The AI Engineer will design, train, implement, and maintain end-to-end machine learning algorithms and their pipelines, automating deployment and monitoring processes while ensuring performance, observability, and security. This role contributes to building scalable infrastructure, real-time dashboards, and automated pipelines that enable secure, compliant, and efficient AI operations aligned with mission and business goals. Key responsibilities include: * Design, build, train, and fine tune computer vision models for object detection, tracking, and classification tasks. * Utilize multimodal architectures for robust retrieval and data fusion. * Coordinate the planning, development, and execution of cutting-edge research programs designed to experimentally validate novel AI/ML concepts. * Evaluate emerging technologies from academia and industry for their potential impact on national security. * Serve as a subject matter expert, providing technical leadership and strategic recommendations to government decision-makers on AI/ML technology, adoption, and implementation. * Set the technical direction for advanced computer vision and AI capabilities supporting exploitation of remote sensing data, including EO and hyperspectral imagery. * Conduct rapid feasibility studies and prototype implementations to evaluate emerging algorithms, model architectures, and data exploitation approaches. * Use prototype-driven demonstrations and technical studies to shape applied research programs and support proposal development for new AI initiatives. * Advance the application of vision-language and multimodal foundation models for analysis, retrieval, and reasoning over large-scale EO/IR and hyperspectral datasets. * Work closely with mission partners to refine problem definitions, evaluate prototype systems, and ensure developed capabilities transition rapidly into operational environments. * Prepare and deliver high-quality technical briefings, documentation, and presentations for both technical and non-technical audiences * Utilizing data pipelines in Databricks, Apache Spark, and related ETL technologies (e.g., AWS Glue, Apache Airflow). * Ensuring compliance with DHS security and accreditation standards, including STIGs and Impact Level controls. * Providing architectural oversight on data ingestion, curation, and storage to produce reliable, high-quality datasets for AI/ML development. * Supporting DevSecOps practices, CI/CD pipelines, and automation to streamline delivery. Note: Candidates must be able to clear and maintain a Public Trust Clearance from the US federal gvmt. This requires US Citizenship and the ability to pass an in-depth background check. Salary Range: $125,000-$150,000 Required Skills * Must be a US Citizen with the ability to obtain and maintain a Public Trust determination * Minimum Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field * 6+ years of experience in software engineering and data engineering * Experience with cloud architecture * Proficiency with AI/ML frameworks (e.g., TensorFlow, PyTorch, YOLO, ONNX) * Proficiency in Linux -- system administration, scripting in Bash, troubleshooting * Strong foundation in AI/ML algorithms and ability to implement agentic workflow, and prompt engineering * Experience in large language model (LLM) applications * Strong understanding of model evaluation metrics (e.g., precision, recall, F1) and statistical drift detection methods * Expertise in containerization and orchestration (Docker, Kubernetes, OpenShift) and CI/CD automation (GitHub Actions, Jenkins) * Proficiency in building and managing ETL pipelines (e.g. AWS Glue, Apache Airflow) * Strong communication skills with the ability to interface and collaborate with project managers, stakeholders, vendors, and technical staff Desired Skills * Master's or PhD degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field * Prior experience supporting DoD, Intelligence Community, or other U.S. Government programs * Experience/familiarity with: * Computer Graphics and Computer Vision AI/ML * Remote sensing (SAR, EO/IR, MSI, etc.) * Network and RF Communications * Signal Processing * Principle component analysis (PCA)/linear discriminant analysis (LDA) * Variational Autoencoders (VAEs) * Bayesian Science/Bayes Naive Network * Retrieval-Augmented Generation (RAG) with Graph DB and Relational DB * Kalman Filtering * Reinforcement Learning (RLHF, PPO, etc.) * PostgreSQL, Elastic, MongoDB, Graph DB for supporting data engineering workflows * Data governance, metadata management, and compliance frameworks ECS Federal LLC is an equal opportunity employer and does not discriminate or allow discrimination on the basis any characteristic protected by law. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local jurisdiction law. is the federal segment of , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies. Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow. We value: * Attracting and developing top talent and high-performing teams * Fostering a culture that is engaging, accountable, and mission-driven Meet the challenge. Make a difference with Everforth ECS! #EverforthECS1