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Ai Monitoring Jobs in Virginia (NOW HIRING)

You will design, build, and maintain production AI/ML services and infrastructure that enable teams to develop, deploy, monitor, and scale models supporting complex defense missions. Working with ...

Implement and support evaluation and monitoring mechanisms to ensure AI solutions meet accuracy and reliability standards. Requirements * Located in Arlington/ Washington DC area * US Citizenship ...

Implement and support evaluation and monitoring mechanisms to ensure AI solutions meet accuracy and reliability standards. Requirements * Located in Arlington/ Washington DC area * US Citizenship ...

AI Architect

Mclean, VA ยท On-site

$190K - $230K/yr

Own AI/MLOps and AI telemetry end-to-end ... Model deployment and versioning, eval pipelines, drift and quality monitoring, cost and latency ...

AI/ML Engineer (Python, AWS, GenAI) Location: Reston, VA (In-person interviews required) Candidate ... Strong understanding of MLOps practices and production model monitoring.

AI Engineer

Reston, VA ยท On-site

AI Solution Development * Design, build, and implement AI/ML models for predictive analytics ... Implement MLOps practices for lifecycle management, monitoring, and continuous improvement.

Senior AI/ML Engineer

Arlington, VA ยท On-site

$120K - $165K/yr

Establish model monitoring, performance tracking, drift detection, explainability, and governance ... Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost ...

Senior AI/ML Engineer

Arlington, VA ยท On-site

$120K - $165K/yr

Establish model monitoring, performance tracking, drift detection, explainability, and governance ... Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost ...

... environmental monitoring, workload management, and resilient mission execution across hybrid ... with AI/ML capabilities applied to policy controlled, workload management and orchestration ...

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate ... Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis ...

Position Summary The AI/ML Engineer will design, build, integrate, evaluate, and maintain ... Support model deployment, monitoring, configuration, and lifecycle management. * Work with data ...

Senior AI/ML Engineer

Arlington, VA ยท On-site

$120K - $165K/yr

Establish model monitoring, performance tracking, drift detection, explainability, and governance ... Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost ...

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate ... Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis ...

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate ... Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis ...

Monitor model performance and iterate based on feedback and metrics. * Stay current with advancements in AI/ML and cloud technologies to ensure our solutions remain cutting-edge. Required ...

AI Infrastructure Engineer

Chantilly, VA ยท On-site

$110K - $144K/yr

AI Infrastructure Engineer Top Secret or TS/SCI is required to start $200K to $250K Chantilly, VA ... Develop and maintain CI/CD pipelines, observability, monitoring, and incident response processes.

Drift monitoring * Retraining triggers * Model governance * Security automation * Collaborate with DevSecOps and cybersecurity teams to integrate AI solutions into secure enterprise delivery ...

AI/ML Engineer The Opportunity: Imagine using artificial intelligence (AI) to improve critical ... Experience with artificial intelligence and machine learning frameworks for monitoring and ...

Showing results 21-40

Ai Monitoring information

What is AI monitoring?

AI monitoring refers to the process of continuously observing and analyzing artificial intelligence systems to ensure they operate as intended. This includes tracking performance, detecting anomalies, ensuring compliance with ethical guidelines, and identifying potential biases or errors. Effective AI monitoring helps organizations maintain transparency, improve system reliability, and ensure that AI models make fair and accurate decisions. It is essential in applications where AI impacts critical business or societal outcomes.

What are some common challenges faced by professionals in AI monitoring roles, and how can they be addressed?

Professionals in AI Monitoring often encounter challenges such as managing large volumes of data, identifying and responding to atypical model behavior, and ensuring compliance with ethical and regulatory standards. Staying updated on the latest AI trends and best practices, utilizing robust monitoring tools, and collaborating closely with data scientists and engineers can help address these challenges. Regular training and open communication within cross-functional teams are also essential to maintain effective oversight and quickly mitigate potential issues.

What are the key skills and qualifications needed to thrive as an AI monitoring specialist, and why are they important?

To thrive as an AI Monitoring Specialist, you need a solid understanding of data analysis, machine learning concepts, and system monitoring, often supported by a degree in computer science or a related field. Familiarity with monitoring platforms like Datadog, Prometheus, or Splunk, as well as experience with scripting languages and AI model management tools, is typically required. Attention to detail, critical thinking, and strong communication skills help specialists identify issues quickly and collaborate with technical teams. These skills and qualities are crucial for ensuring AI systems operate reliably, securely, and efficiently in real-world applications.

What is the difference between Ai Monitoring vs Data Analyst?

AspectAi MonitoringData Analyst
Required CredentialsTypically requires knowledge of AI systems, programming, and data analysis toolsRequires statistical, analytical, and data visualization skills, often with a degree in data science or related fields
Work EnvironmentOften involves monitoring AI systems in real-time, using specialized software, in tech or AI-focused companiesAnalyzes data sets, creates reports, and provides insights, working in various industries like finance, marketing, or healthcare
Employer & Industry UsageCommon in AI development firms, tech companies, and organizations deploying AI solutionsWidely used across industries for decision-making, reporting, and strategic planning

While both roles involve working with data, Ai Monitoring focuses on overseeing AI system performance and ensuring operational accuracy, whereas Data Analysts interpret data to support business decisions. Understanding these differences helps in choosing the right career path or job search focus.

What are popular job titles related to Ai Monitoring jobs in Virginia?

For Ai Monitoring jobs in Virginia, the most frequently searched job titles are:

Infographic showing various Ai Monitoring job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, and 4% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

AI/ML Engineer

Arlington, VA โ€ข On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 14 days ago


Key responsibilities

  • Design, build, and maintain AI/ML services, products, and lifecycle capabilities supporting WDP

  • Develop automated pipelines for model training, validation, testing, deployment, and monitoring

  • Troubleshoot issues spanning models, applications, data pipelines, infrastructure, and production services


Job description

540 is seeking an AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will design, build, and maintain production AI/ML services and infrastructure that enable teams to develop, deploy, monitor, and scale models supporting complex defense missions.

Working with software engineers, data engineers, data scientists, cybersecurity teams, and mission stakeholders, you will build reusable ML capabilities and automated pipelines using modern software engineering and MLOps practices. The ideal candidate enjoys solving complex engineering challenges and building secure, reliable AI/ML systems that directly support mission outcomes.

Location: Arlington, VA
Citizenship & Clearance Requirement: Per client requirements, candidates must be U.S. Citizens with an active DoW Secret (or higher) clearance
Education Requirement: Bachelor's degree in Computer Science, Engineering, or a related technical field preferred; equivalent combinations of education and relevant experience will be considered
540 Internal Thrive Level: Software Engineer II or III

WHY 540?

540 is a forward-thinking company that the government turns to in order to #getshitdone. We don't just talk about innovation - we deliver it. We break down barriers, build impactful technology, and solve mission-critical problems.

HOW YOU'LL DRIVE IMPACT

  • Design, build, and maintain AI/ML services, products, and lifecycle capabilities supporting WDP
  • Develop automated pipelines for model training, validation, testing, deployment, and monitoring
  • Create reusable frameworks, libraries, and shared components that accelerate AI/ML development
  • Build model-serving capabilities supporting secure, scalable, and reliable batch or real-time inference
  • Implement MLOps practices using CI/CD, infrastructure as code, automated testing, and source control
  • Develop model monitoring, performance tracking, drift detection, and operational health capabilities
  • Support model explainability, reproducibility, governance, and lifecycle traceability
  • Manage model versions, artifacts, datasets, and feature-engineering workflows
  • Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost efficiency
  • Collaborate with data engineers and data scientists to prepare data and operationalize models
  • Partner with cybersecurity teams to implement security, access-control, auditing, and governance requirements
  • Troubleshoot issues spanning models, applications, data pipelines, infrastructure, and production services
  • Document AI/ML architectures, engineering processes, and operational procedures

REQUIRED SKILLS & EXPERIENCE

  • 4+ years of relevant AI/ML engineering, software engineering, or data science experience
  • Experience developing and deploying production-grade AI or machine learning systems
  • Proficiency with Python and commonly used AI/ML frameworks
  • Experience building automated model training, validation, deployment, and monitoring pipelines
  • Experience with MLOps platforms, practices, and tools
  • Experience deploying models in cloud-based or containerized environments
  • Experience developing APIs, microservices, or model-serving capabilities for batch or real-time inference
  • Understanding of model evaluation, performance monitoring, drift detection, explainability, and governance
  • Experience with Docker, Kubernetes, or similar containerization and orchestration technologies
  • Experience with CI/CD, infrastructure as code, automated testing, and source control
  • Experience working within AWS, Azure, or Google Cloud
  • Familiarity with data pipelines, feature engineering, distributed data processing, and data versioning
  • Ability to troubleshoot issues across applications, infrastructure, data, and machine learning systems
  • Strong communication and collaboration skills, including the ability to document and explain technical decisions

NICE TO HAVE

  • Experience supporting DoW, federal, Advana, or other enterprise AI/ML and data platforms
  • Experience with AWS SageMaker or comparable cloud AI/ML platforms
  • Experience with MLflow, Kubeflow, Airflow, Argo Workflows, Ray, Feast, or similar tools
  • Experience building AI/ML solutions in secure, regulated, classified, or mission-critical environments
  • Familiarity with large language models, generative AI, retrieval-augmented generation, or foundation-model operations
  • Experience implementing responsible AI, model-risk-management, or AI-governance practices
  • Currently holds, or is willing to obtain within 30 days of employment, an approved certification such as CCSP, CFR, FITSP-M, GSEC, Security+, or SSCP

BENEFITS & PERKS

  • Flexible PTO + all Federal holidays off
  • Health, dental and vision insurance plans
  • Flexible Spending Account (FSA)
  • 401k with employer match
  • Company-sponsored life insurance, short- and long-term disabilityย 
  • Professional development (training, certifications, conferences)
  • Paid cloud developer accounts
  • Referral bonuses
  • HQ office perks (parking / metro reimbursement, nitro coffee & lunches)ย 
  • Annual social events (540 Week, hackathon, charity golf tournament, etc.)
  • Access to 540's Washington Capitals & Nationals tickets

EQUAL EMPLOYMENT OPPORTUNITY (EEO)

540's policy is to provide equal employment opportunity to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.