Skills & Experience Requirements :
4 years building tuning and deploying machine learning models in production environments. Strong background in MLOps practices using MLflow or similar tools for model versioning deployment and governance.
Experience with microservices-based AI architectures and integration into operational platforms. Proficiency in containerization (Docker Kubernetes) and scalable inference serving. Knowledge of explainability frameworks (e.g. SHAP LIME) and bias detection techniques in AI systems. Preferred Qualifications
Experience deploying AI models in regulated mission environments (healthcare federal security customs
Familiarity with real-time risk scoring and decision-support integrations for government screening systems.
Hands-on use of graph transformers or hybrid ruleAI architectures.
Background in scaling AI solutions across multiple product categories or mission areas