AI/ML Engineer

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