Senior AI/ML Engineer
On-siteArlington, Virginia, United States
Job Summary
Lead the architecture and evolution of production AI/ML services and infrastructure supporting complex defense missions. Translate mission requirements into secure, scalable solutions by defining MLOps standards, establishing reusable frameworks, and architecting automated pipelines for model training, validation, testing, and deployment. Design model-serving platforms for batch and real-time inference while implementing monitoring, drift detection, and governance capabilities. Optimize services for performance and reliability, establish CI/CD and infrastructure-as-code practices, and partner with cybersecurity teams to enforce access control and auditing. Mentor engineers and resolve complex issues spanning models, applications, and production systems.
Required Qualifications
- U.S. Citizens
- active DoW Secret (or higher) clearance
- 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
Desired Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- 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
- Experience building AI/ML platforms in secure, regulated, classified, or mission-critical environments
- Experience with large language models, generative AI, retrieval-augmented generation, or foundation-model operations
- Experience establishing responsible AI, model-risk-management, or AI-governance practices
- Experience leading AI/ML platform modernization, technology evaluations, or proofs of concept
- 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
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