AI/ML Platform Engineer

Johns Hopkins Applied Physics Laboratory (APL) seeks an AI/ML Platform Engineer to design, build, and operate secure, scalable machine learning platforms that power mission-critical research in national security, space, and health. You will create cloud-native and on-prem MLOps pipelines, automate infrastructure, and productionize models in partnership with data scientists and researchers. In APL's collaborative, mission-driven environment, you'll solve complex real-world problems while advancing your skills through research, advanced degrees, and professional development.

Responsibilities

• Design, build, and maintain scalable AI/ML platforms to support research and mission applications
• Develop CI/CD and MLOps pipelines for model training, evaluation, and deployment
• Implement observability, monitoring, and reliability practices for ML services
• Collaborate with data scientists and engineers to productionize models and workflows
• Optimize compute, storage, and data pipelines for performance and cost efficiency
• Ensure security, compliance, and governance of AI/ML environments and data
• Automate environment provisioning using infrastructure-as-code tools
• Contribute to technical roadmaps, architecture decisions, and platform standards

Required Skills

• Machine learning platforms (Kubeflow, MLflow, Sage
• Maker, Vertex AI, or similar)
• MLOps and CI/CD for ML (Git
• Lab CI, Git
• Hub Actions, Jenkins, or similar)
• Python for data/ML engineering
• Containerization and orchestration (Docker, Kubernetes)
• Cloud computing (AWS, Azure, or GCP)
• Infrastructure as code (Terraform, Cloud
• Formation, or similar)
• Data pipelines and ETL (Spark, Airflow, or similar)
• Monitoring and observability (Prometheus, Grafana, Cloud
• Watch, etc.)
• Linux systems and shell scripting
• Security, compliance, and access control for data and ML systems