MLOpsEngineer

**_Job Family_ :** Data Science & Analysis ** _Travel Required_ :** Up to 25% **_Clearance Required_ :** Active Secret What You Will Do: As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and operational processes that enable scalable, secure, and reliable deployment of machine learning solutions for federal clients. You will partner closely with data scientists, AI engineers, data engineers, and government stakeholders to operationalize models across development, testing, and production environments. You will play a critical role in enabling secure AI and ML delivery within DoD and federal financial environments, ensuring models are repeatable, auditable, and compliant with federal standards. Key responsibilities include: * Design, build, and maintain end‑to‑end MLOps pipelines, supporting model training, testing, deployment, monitoring, and retraining * Implement CI/CD workflows for ML models and data pipelines in secure federal environments * Operationalize machine learning models built by data science teams and ensure production readiness * Develop and manage model versioning, artifact management, and experiment tracking * Implement monitoring solutions for model performance, drift, data quality, and pipeline health * Automate infrastructure provisioning and deployment using infrastructure‑as‑code and DevOps best practices * Support auditability, explainability, and governance of AI/ML systems * Collaborate with stakeholders to align MLOps architectures with mission needs and security requirements ## ## _What You Will Need:_ * US Citizenship required * An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance. * Bachelor’s degree obtained. * 3–5 years of experience in MLOps, ML engineering, data engineering, DevOps, or related technical roles * Strong experience with Python and ML tooling supporting model packaging, deployment, and monitoring * Hands‑on experience building CI/CD pipelines for data and ML workloads *