Remote ML Ops Engineer: Cloud AI Platform & MLOps

ICF Olson; United States; Remote; USD 99,000 - 168,000; Full time

Job summary

ICF is seeking an experienced ML Ops Engineer to design and maintain production-grade ML pipelines across training, evaluation, deployment, monitoring, and retraining. You will implement automated CI/CD for model artifacts using GitHub Actions, Terraform, and Databricks tooling, and ensure robust, scalable model serving in cloud environments.

Preference for DC metro area with remote work options. The role emphasizes Trustworthy AI practices, model governance, and integration with enterprise

Qualifications

• U.S. Citizenship is required due to federal contract requirements.
• Bachelor's degree or higher in a related field with 6+ years of ML in cloud environments.
• Master's degree may substitute for two years of experience.
• Experience with MLOps, automated deployment pipelines, and model lifecycle management.

Responsibilities

• Design and maintain production-grade MLOps pipelines for training, evaluation, and deployment.
• Develop reusable MLOps patterns using Azure Databricks, MLflow, and Unity Catalog.
• Build automated CI/CD pipelines with GitHub Actions, Azure DevOps, Terraform.
• Deploy scalable model-serving infrastructure for batch, streaming, and real-time workloads.
• Implement monitoring, governance, and trustworthiness controls across models.

Skills

MLOps

Python

CI/CD practices

Cloud architecture

Trustworthy AI

Education

Bachelor's degree in Computer Science, Software Engineering, ML, Data Science, Engineering or related field

Master's degree may substitute for 2 years of relevant experience

Tools

GitHub Actions

Azure DevOps

Terraform

Databricks

MLflow

Unity Catalog

Azure Machine Learning

Job description

ICF is seeking an experienced ML Ops Engineer to design and maintain production-grade ML pipelines across training, evaluation, deployment, monitoring, and retraining. You will implement automated CI/CD for model artifacts using GitHub Actions, Terraform, and Databricks tooling, and ensure robust, scalable model serving in cloud environments.

Preference for DC metro area with remote work options. The role emphasizes Trustworthy AI practices, model governance, and integration with enterprise