MLOps Engineer
Core
Design, implement, and support platforms and pipelines for scalable, secure, and reliable deployment of machine learning solutions for federal clients.
Role type
MLOps Engineer
Builds
End-to-end MLOps pipelines, CI/CD workflows, and operationalized ML models for DoD and federal financial environments
Domain
Federal Government / Defense / Financial Services
Deliverable
production ML models
Required skills
Python, CI/CD pipelines, containerization and orchestration (Docker, Kubernetes), infrastructure-as-code, model versioning, artifact management, experiment tracking, monitoring solutions (performance, drift, data quality), secure cloud/hybrid environments
Preferred skills
Databricks (MLflow, Spark, Delta Lake), Palantir Foundry, Azure Government/AWS GovCloud, responsible AI, model risk management
Technologies
Python, Docker, Kubernetes, MLflow, Spark, Delta Lake, Palantir Foundry, Azure, AWS
Responsibilities
Design and maintain end-to-end MLOps pipelines; Implement CI/CD workflows for ML models and data pipelines; Operationalize machine learning models; Develop and manage model versioning and artifact management; Implement monitoring for model performance and pipeline health; Automate infrastructure provisioning using infrastructure-as-code; Support auditability and governance of AI/ML systems
Seniority
Mid-level, hands-on IC