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Model Engineering Jobs in Virginia (NOW HIRING)

Solvarus

Model Based System Engineer

Chantilly, VA · On-site

Create engineering artifacts and develop models of mission systems using a MBSE tool suite that includes NoMagic Cameo EA, Rhapsody, Sparx EA as well as other systems engineering tools. * Define the ...

Solvarus

Model Based System Engineer

Chantilly, VA · On-site

Create engineering artifacts and develop models of mission systems using a MBSE tool suite that includes NoMagic Cameo EA, Rhapsody, Sparx EA as well as other systems engineering tools. * Define the ...

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Model Engineering information

See Virginia salary details

$10

$31

$66

How much do model engineering jobs pay per hour?

As of Jul 9, 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 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 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 engineers make $200,000 a year?

Senior engineers in specialized fields such as petroleum, aerospace, or software engineering often earn $200,000 or more annually, especially with extensive experience, advanced skills, and relevant certifications. High-level managerial or executive engineering roles can also reach or exceed this salary level, typically requiring leadership responsibilities and a strong track record.

What engineers make $500,000?

Senior engineers in specialized fields such as petroleum, aerospace, or software engineering can earn $500,000 or more annually, often through a combination of base salary, bonuses, and stock options. High-level roles typically require extensive experience, advanced skills, and sometimes professional certifications or advanced degrees.

What engineers make $300,000 a year?

Senior engineers in specialized fields such as petroleum engineering, aerospace engineering, and software engineering with extensive experience and advanced skills can earn $300,000 or more annually. High-level roles often require advanced degrees, certifications, and leadership responsibilities, especially in industries like oil and gas, aerospace, and technology companies.

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 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 does a modeling engineer do?

A modeling engineer designs and develops mathematical and computer models to simulate real-world systems or processes. They use tools like CAD software and programming languages to create accurate representations, often working in industries such as manufacturing, aerospace, or automotive. Their work supports product development, optimization, and testing efforts.
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:
Model Engineering jobs near you
Infographic showing various Model Engineering job openings in Virginia as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $64,686 per year, or $31.1 per hour.
AI / ML Engineer Manager

AI / ML Engineer Manager

Accenture Federal Services

Arlington, VA

Other

Re-posted 23 days ago

Accenture Federal Services rating

8.4

Company rating: 8.4 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

48th of 442 rated business services

Job description

As the Manager for the AI/ML Models as a Service (MaaS) team, you will lead a specialized group of developers and engineers dedicated to productionizing machine learning for the DoD. Your mission is to build and manage a centralized platform that provides access to pre-trained and custom-built AI/ML models, simplifying their integration and accelerating the delivery of AI-powered capabilities across the enterprise . This is a strategic, hands-on leadership role where you will define the vision for our MaaS offerings and oversee the entire lifecycle of model development, deployment, and operations.

Responsibilities:

  • Lead, mentor, and manage a high-performing team of ML modeling developers and MLOps engineers.
  • Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring.
  • Oversee the design, development, and deployment of a diverse portfolio of machine learning models to solve complex mission challenges.
  • Establish and enforce robust MLOps practices to ensure automated, reliable, and scalable CI/CD pipelines for machine learning models.
  • Architect the service layer for the MaaS platform, ensuring models are exposed via secure, scalable, and well-documented APIs.
  • Collaborate with data scientists, data engineers, and mission stakeholders to identify use cases and translate requirements into production-ready models.
  • Implement governance, security, and ethical AI standards across the entire model lifecycle.
  • Manage project timelines, resource allocation, and stakeholder communication for all MaaS initiatives.

Required Qualifications:

  • 8+ years of experience in data science or machine learning engineering, with at least 3 years in a technical leadership or management role.
  • Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP).
  • Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML).
  • Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD tools.
  • Experience with programming skills in Python and familiarity with software engineering best practices. 
  • US Citizenship (No Dual Citizenship)

Preferred Qualifications:

  • Direct experience building a Model-as-a-Service or Machine-Learning-as-a-Service platform.
  • Experience with ML platforms like Databricks or AWS SageMaker AI.
  • Familiarity with Infrastructure-as-Code (IaC) tools like Terraform.
  • Experience working in a high-security DoD or Intelligence Community environment.
  • Demonstrated success leading teams that deliver complex, data-driven software projects.

Security Clearance:

  • Active TS or TS/SCI Clearance

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