MLOps Engineer — AI/ML Systems & Deployment (TS/SCI Preferred)

📋 Description

• Own the ML lifecycle end-to-end from experimentation to production.
• Orchestrate ML workflows with Kubeflow, Airflow, or Argo.
• Deploy models in mission environments (constrained/classified).
• Build and operate production-grade ML pipelines.
• Enable batch and real-time inference architectures.
• Design for reproducibility, auditability, stability.

🎯 Requirements

• Production ML deployment experience.
• Strong Python and ML frameworks (PyTorch, TensorFlow).
• Orchestration with Kubeflow, Airflow, Argo.
• Experiment tracking with MLflow, ClearML.
• Kubernetes, containerized infra, and ML CI/CD.
• Data/versioning and governance (lakeFS) with STAC metadata.

🎁 Benefits

• 100% covered certifications & training aligned to your role.
• 401(k) with 100% match up to 6%.
• Highly competitive PTO.
• Comprehensive Medical, Dental, Vision coverage.
• Life Insurance + Short & Long-Term Disability.
• Home office & equipment plan.
• Industry-leading weekly pay schedule.