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Ml Infrastructure Jobs in Virginia (NOW HIRING)

Noblis

AI/ML Engineer, Senior

Chantilly, VA · On-site

$107K - $146K/yr

Infrastructure & Operations * Architect and implement cloud-native ML infrastructure on AWS. * Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment ...

Noblis

AI/ML Engineer (Clearance Required)

Reston, VA · On-site

Infrastructure & Operations * Architect and implement cloud-native ML infrastructure on AWS. * Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment ...

Noblis

AI/ML Engineer (Clearance Required)

Reston, VA · On-site

Infrastructure & Operations * Architect and implement cloud-native ML infrastructure on AWS. * Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment ...

Noblis

AI/ML Engineer, Senior

Chantilly, VA · On-site

$107K - $146K/yr

Infrastructure & Operations * Architect and implement cloud-native ML infrastructure on AWS. * Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment ...

Halvik-

AI/ML Subject Matter Expert

Vienna, VA · On-site

$100 - $130/hr

Make informed ML infrastructure decisions based on modeling techniques and issues * Write and test application code, develop ML models, and automate tests and deployment * Retrain, maintain, and ...

Halvik

AI/ML Subject Matter Expert

Vienna, VA · On-site

$195K - $210K/yr

Make informed ML infrastructure decisions based on modeling techniques and issues * Write and test application code, develop ML models, and automate tests and deployment * Retrain, maintain, and ...

Noblis

Data Scientist (AI/ML)

Chantilly, VA · On-site

Support production AI/ML infrastructure and operations , including platform maintenance, issue triage, troubleshooting, and user support. * Support Kubernetes-based platform operations , including ...

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Ml Infrastructure information

What is ML infrastructure?

ML Infrastructure refers to the underlying systems, tools, and processes that enable the development, deployment, and scaling of machine learning models. This includes data storage and management, computing resources, model training and serving environments, monitoring, and automation tools. ML Infrastructure ensures that data scientists and engineers can efficiently build, test, and maintain machine learning applications in a reliable and reproducible manner. It is a crucial foundation for organizations looking to operationalize AI and machine learning solutions at scale.

What are some common challenges faced by professionals working in ML infrastructure roles?

Professionals in ML Infrastructure often encounter challenges related to scaling systems to handle large volumes of data, ensuring reliable deployment pipelines, and maintaining reproducibility across different environments. They must also collaborate closely with data scientists and engineers to streamline workflows and address issues like version control and model monitoring. Staying updated with rapidly evolving tools and best practices is essential, and balancing stability with innovation is a frequent aspect of the role.

What are the key skills and qualifications needed to thrive as an ML infrastructure engineer, and why are they important?

To thrive as an ML Infrastructure Engineer, you need a strong background in software engineering, cloud computing, and machine learning concepts, often supported by a degree in computer science or a related field. Proficiency with containerization tools (like Docker and Kubernetes), cloud platforms (such as AWS, GCP, or Azure), and CI/CD systems is critical. Excellent problem-solving, collaboration, and communication skills help you efficiently work with data scientists and DevOps teams. These skills and qualities are vital for building scalable, reliable ML systems that support rapid experimentation and deployment in production environments.

What is the difference between Ml Infrastructure vs Data Engineer?

AspectML InfrastructureData Engineer
Required CredentialsBachelor's in CS, Data Science, or related; knowledge of cloud platformsBachelor's in CS, Software Engineering, or related; experience with databases and ETL tools
Work EnvironmentFocus on deploying and maintaining ML systems, cloud environments, and infrastructure toolsDesigning, building, and managing data pipelines and storage solutions
Industry UsageUsed in AI/ML teams to support model deployment and scalabilityUsed across data-driven organizations for data management and analytics

ML Infrastructure specialists focus on deploying, scaling, and maintaining machine learning systems and infrastructure, while Data Engineers primarily build and manage data pipelines and storage solutions. Both roles require technical skills and often collaborate, but their core responsibilities differ in focus and tools used.

What are popular job titles related to Ml Infrastructure jobs in Virginia?

For Ml Infrastructure jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Ml Infrastructure jobs in Virginia look for?

The top searched job categories for Ml Infrastructure jobs in Virginia are:

What cities in Virginia are hiring for Ml Infrastructure jobs?

Cities in Virginia with the most Ml Infrastructure job openings:

Ml Infrastructure jobs near you
Infographic showing various Ml Infrastructure job openings in Virginia as of August 2026, with employment types broken down into 83% Full Time, 14% Part Time, and 3% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution.

AI/ML Engineer, Senior (TS/SCI w/ poly) - Chantilly, VA

Veteran Jobs - 2023 Mar 01 - Veterans Resources

Chantilly, VA • On-site

$160K - $251K/yr

Full-time

Re-posted 4 days ago

Job description

ATTENTION MILITARY AFFILIATED JOB SEEKERS - Our organization works with partner companies to source qualified talent for their open roles. The following position is available to Veterans, Transitioning Military, National Guard and Reserve Members, Military Spouses, Wounded Warriors, and their Caregivers. If you have the required skill set, education requirements, and experience, please click the submit button and follow the next steps. Unless specifically stated otherwise, this role is On-Site
AI/ML Engineer, Senior
 
  • Noblis is seeking an experienced AI/ML Engineer with Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph  to support mission-critical national security initiatives.
 
In this role, you will design, develop, and deploy advanced machine learning solutions while building the infrastructure required to operationalize AI capabilities in secure, production environments. 
Job Responsibilities: 
 
  • Model Development & Deployment
    • Design, develop, and containerize machine learning (ML) models using modern frameworks and tools, including PyTorch, Ray, Docker, and FastAPI. 
    • Deploy, manage, and scale production ML workloads on Kubernetes. 
    • Integrate AI/ML capabilities into full-stack applications using Python-based backend services and JavaScript frontend technologies. 
    • Ensure model reliability, performance, and maintainability throughout the deployment lifecycle. 
 
  • Infrastructure & Operations
    • Architect and implement cloud-native ML infrastructure on AWS. 
    • Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment, and monitoring. 
    • Deploy and support AI/ML systems within secure, classified, and high side environments. 
 
  • Technical Leadership
    • Evaluate and adopt state-of-the-art AI/ML models, frameworks, and emerging technologies. 
    • Architect scalable and resilient infrastructure to support evolving AI/ML workloads and mission requirements. 
    • Establish and promote best practices for production-grade machine learning (ML) systems, including security, observability, and governance. 
    • Provide technical guidance and thought leadership across AI/ML initiatives and engineering teams. 

Required Qualifications
  • Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph
  • Bachelor's degree with 8 years of related experience; OR Master's degree with 7 years of related experience; OR associate's degree with 11 years of related experience; OR High School diploma/GED with 14 years of related experience
  • Production experience deploying ML models, including LLMs
  • Strong proficiency with ML frameworks and containerization (e.g., PyTorch, Docker, Kubernetes)
  • Full-stack development experience (e.g., Python, JavaScript)
  • Working knowledge of AWS cloud services
  • Demonstrated MLOps/DevOps implementation experience
  • U.S. Citizenship is required

Desired Qualifications
  • AWS Certification, including AWS Certified DevOps Engineer or AWS Certified Solutions Architect Certification

Posted Salary Range
USD $160,800.00 - USD $251,325.00 /Yr.

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