Senior AI/ML Engineer

540 is seeking a Senior AI/ML Engineer to support a mission-critical technology modernization effort for the Department of War. You will lead the design and evolution of 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 translate complex requirements into secure, scalable AI/ML solutions. You will define MLOps standards, guide technical delivery, and establish reusable capabilities supporting the end-to-end machine learning lifecycle.

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: Senior Software Engineer

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

• Lead the architecture and evolution of AI/ML services, platforms, and lifecycle capabilities supporting WDP
• Translate mission requirements into scalable AI/ML architectures and implementation strategies
• Define MLOps standards, reusable patterns, and best practices across engineering teams
• Architect automated pipelines for model training, validation, testing, deployment, and monitoring
• Develop reusable frameworks, libraries, and shared components that accelerate AI/ML delivery
• Design model-serving platforms supporting secure, scalable, and reliable batch or real-time inference
• Establish model monitoring, performance tracking, drift detection, explainability, and governance capabilities
• Define practices for model versioning, artifact management, reproducibility, feature engineering, and data lineage
• Optimize AI/ML services and infrastructure for performance, scalability, reliability, and cost efficiency
• Establish CI/CD, infrastructure-as-code, automated testing, and operational practices for AI/ML systems
• Lead technical reviews and resolve complex issues spanning models, applications, data, infrastructure, and production services
• Partner with cybersecurity teams to incorporate security, access control, auditing, and governance requirements
• Communicate architecture decisions and mentor engineers and data scientists on AI/ML engineering and MLOps practices

REQUIRED SKILLS & EXPERIENCE

• 9+ years of relevant AI/ML engineering, software engineering, or data science experience
• Experience leading the design and delivery of enterprise-scale, production-grade AI/ML systems
• Advanced software engineering experience using Python and commonly used AI/ML frameworks
• Experience architecting automated model training, validation, deployment, and monitoring pipelines
• Experience defining MLOps architecture, standards, and practices across engineering teams
• Experience designing model-serving capabilities for batch and real-time inference
• Experience deploying and operating models in cloud-based or containerized environments
• Strong understanding of model evaluation, monitoring, drift detection, explainability, reproducibility, and governance
• Experience with Docker, Kubernetes, or similar containerization and orchestration technologies
• Experience establishing CI/CD, infrastructure-as-code, automated testing, and source-control practices
• Experience architecting AI/ML solutions within AWS, Azure, or Google Cloud
• Experience with data pipelines, distributed data processing, feature engineering, and data versioning
• Ability to evaluate technical approaches and clearly communicate architecture decisions, risks, and tradeoffs
• Experience leading technical reviews, mentoring engineers, and influencing technical direction
• Ability to troubleshoot complex issues across applications, infrastructure, data, and machine learning systems

NICE TO HAVE

• Experience leading AI/ML initiatives within DoW, federal, Advana, or other enterprise data environments
• Experience architecting solutions using AWS SageMaker or comparable cloud AI/ML platforms
• Experience with MLflow, Kubeflow, Airflow, Argo Workflows, Ray, Feast, or similar technologies